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-1- IN THE HIGH COURT OF KARNATAKA AT BENGALURU DATED THIS THE 26TH DAY OF SEPTEMBER, 2019 PRESENT THE HON'BLE MR.ABHAY S. OKA, CHIEF JUSTICE AND THE HON'BLE MR. JUSTICE S.R.KRISHNA KUMAR WRIT PETITION NO.49554 OF 2018 & WRIT PETITION NOS.13757-13900 OF 2019 (GM-POL) BETWEEN: 1.
P.RAJANNA S/O.P.PILLAPPA AGED ABOUT 69 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
2. B.MUNIVENKATAPPA S/O.BYRAPPA AGED ABOUT 72 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
3. P.ANAND S/O.LATE PILLAPPA AGED ABOUT 44 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
4. CHETHANGOWDA V.
S/O.VENKATESH C. AGED ABOUT 24 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI -2- DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
5. LAKSHMANA P.
S/O.LATE PILLAPPA AGED ABOUT 40 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
6. SUSHMITHA P.
D/O.PRAKASH AGED ABOUT 27 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
7. NETHRAVATHI W/O.SATHYANARAYANA AGED ABOUT 33 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
8. NARAYANASWAMY P.
S/O.PAPANNA AGED ABOUT 43 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
9. MURALI B.M.
S/O.MUNISHAMAPPA AGED ABOUT 31 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
10. NAVEEN M. GOWDA S/O.MARIYAPPA AGED ABOUT 33 YEARS -3- BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
11. B.N.MANJUNATH S/O.NARAYANASWAMY P. AGED ABOUT 28 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
12. D.A.MANJUNATH GOWDA S/O.LATE P.ANJINAPPA AGED ABOUT 29 YEARS DANDIGANAHALLI VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
13. B.RAMAKRISHNAPPA S/O.BYRAPPA AGED ABOUT 71 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
14. B.M.BASAVARAJU S/O.MUNIYAPPA AGED ABOUT 45 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
15. SAVITHA W/O.BASAVARAJU B.M. AGED ABOUT 29 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
16. MADAN B.
S/O.BYRAPPA -4- AGED ABOUT 22 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
17. NAGARAJU C.
S/O.CHIKKAVENKATAPPA AGED ABOUT 39 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
18. SOMASHEKAR R.
S/O.RAJANNA P.
AGED ABOUT 40 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
19. MANJUNATH B.K.
S/O.KRISHNAPPA AGED ABOUT 32 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
20. SATHISH N.
S/O.NARAYANAPPA AGED ABOUT 32 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
21. RATHNAMMA W/O.PAPANNA AGED ABOUT 51 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135 -5-
22. SUNIL N.
S/O.NARAYANAPPA AGED ABOUT 29 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
23. MUNIRAJU J.
S/O.GOVINDAPPA AGED ABOUT 40 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
24. PUSHPA N.
W/O.MUNIRAJU J. AGED ABOUT 26 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
25. SHRIRAMAPPA P.
S/O.LATE PILLAPPA AGED ABOUT 59 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
26. NALINA G.
W/O.SOMASHEKAR AGED ABOUT 30 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
27. SOMASHEKAR C.
S/O.CHIKKA BAYANNA AGED ABOUT 40 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135 -6-
28. SAVITHA A.
W/O.ANAND AGED ABOUT 35 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
29. BHAGYALAKSHMI K.M.
D/O.MUNINARAYANAPPA AGED ABOUT 28 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
30. MUNIANJINAPPA P.
S/O.PAPANNA AGED ABOUT 35 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
31. ASHA M.
D/O.MUNIVENKATAPPA AGED ABOUT 25 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
32. KONDAPPA M.
S/O.MUNIVENKATAPPA AGED ABOUT 40 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
33. NARAYANSWAMY M.
S/O.MUNIVENKATAPPA AGED ABOUT 46 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135 -7-
34. VENKATARATHNAMMA W/O.NARAYANASWAMY AGED ABOUT 43 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
35. CHANDRASHEKAR N.
S/O.NARAYANAPPA AGED ABOUT 36 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
36. B.M.NARAYANASWAMY S/O.MUNIYAMMA AGED ABOUT 49 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
37. PARWATHAMMA D/O.THAMMANNA AGED ABOUT 68 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
38. MANOHAR M.
S/O.MUNISHAMAPPA AGED ABOUT 29 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
39. MUNISHAMAPPA AGED ABOUT 58 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135 -8-
40. SAVITRAMMA W/O.NAGARAJU AGED ABOUT 38 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
41. NAGARAJU S/O.MUNIBASAPPA AGED ABOUT 53 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
42. NARAYANASWAMY S/O.LATE CHIKAVENKATAPPA AGED ABOUT 45 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
43. NIRMALA W/O.NARAYANASWAMY AGED ABOUT 36 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
44. ANJINAMMA W/O.LATE CHIKAVENKATAPPA AGED ABOUT 64 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
45. GOVINDRAJ C.
S/O.LATE CHOWDAPPA AGED ABOUT 44 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135 -9-
46. VENKATESH C.
S/O.LATE CHOWDAPPA AGED ABOUT 50 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
47. ASHWATHAPPA M.
S/O.LATE MUNISHAMAPPA AGED ABOUT 48 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
48. NARAYANAPPA S/O.DODDAAVALAPPA AGED ABOUT 71 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
49. LEELAVATHI K.
W/O.VENKATESH AGED ABOUT 45 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
50. MALA J.
W/O.GOVINDRAJU C. AGED ABOUT 33 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
51. VINITH GOWDA V.
S/O.VENKATESH AGED ABOUT 19 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
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52. ASHA S.
W/O.ASHWATHAPPA AGED ABOUT 42 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
53. SATHYANARAYANA R.
S/O.BYRAPPA AGED ABOUT 38 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
54. GANGADHAR N.
S/O.NARASIMHAIAH AGED ABOUT 38 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
55. NAVEENKUMAR N.
S/O.NARASIMHAIAH AGED ABOUT 28 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
56. NARASIMHAIAH S/O.DODDA KADIRAPPA AGED ABOUT 53 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
57. GAYITHRI D/O.THIRUMALAPPA AGED ABOUT 29 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
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58. PAPAMMA W/O.NARASIMHAIAH AGED ABOUT 48 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
59. NAGARAJU N.
S/O.NARASIMHAIAH AGED ABOUT 32 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
60. HEMAVATHI W/O.GANGADHAR AGED ABOUT 36 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
61. PRATHIBHA T.
D/O.THIRUMALAPPA AGED ABOUT 25 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
62. DEVRAJU N.
S/O.NARAYANAPPA AGED ABOUT 36 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
63. DEEPA S.
W/O.NAGARAJU AGED ABOUT 30 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
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64. MUNIVENKATAPPA S/O.MUNIYAPPA AGED ABOUT 46 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
65. PRAVEEN KUMAR M.
S/O.MARIYAPPA AGED ABOUT 30 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
66. S.RAMANJINAPPA S/O.SANJEEVAPPA AGED ABOUT 48 YEARS HAROHALLI VILLAGE & POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
67. S.HANUMEGOWDA S/O.SANJIVAPPA AGED ABOUT 43 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
68. KRISHNAPPA S/O.NARAYANAPPA AGED ABOUT 65 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
69. R. RAMACHANDRAPPA S/O.RAMAKRISHNAPPA AGED ABOUT 56 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
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70. KRISHNAPPA S/O.NARAYANAPPA AGED ABOUT 65 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
71. SOUBHAGYA S.K.
D/O.KRISHNAPPA AGED ABOUT 43 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
72. DAYANANDA S/O.NANJAPPA N. AGED ABOUT 46 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
73. MOHAN KUMAR H.J.
S/O.JAYARAMAREDDY H.D. AGED ABOUT 32 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
74. MUNINARAYANAPPA H.A.
S/O.LATE APPAJAPPA AGED ABOUT 58 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
75. MUNITHAYAMMA W/O.MUNINARAYANAPPA H.A. AGED ABOUT 55 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
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76. SUBRAMANI S/O.SANJIVAPPA AGED ABOUT 55 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
77. B.PRAVEEN S/O.BASAVARAJU AGED ABOUT 32 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
78. USHA K.
S/O.KRISHNAPPA AGED ABOUT 27 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
79. BASAVARAJU S/O.MUNIBASAPPA AGED ABOUT 60 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
80. CHANDRAMMA D/O.LAKSHMANA AGED ABOUT 55 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
81. PRAKASH B.
S/O.BASAVARAJU AGED ABOUT 35 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
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82. RAJU H.P.
S/O.PILLAPPA AGED ABOUT 33 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
83. BYREGOWDA H.M.
S/O.MUNISHAMAPPA AGED ABOUT 64 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
84. ANNAPOORNA G.
D/O.GOPAL K.H.
AGED ABOUT 38 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
85. BHARATH H.R.
S/O.RAMANJINAPPA AGED ABOUT 19 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
86. BHARATH KUMAR H.J.
S/O.JAYARAMAREDDY AGED ABOUT 29 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
87. S. HARISH S/O.SRIRAMAPPA AGED ABOUT 28 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
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88. SUNIL KUMAR S.
S/O.SRIRAMAPPA AGED ABOUT 26 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
89. RAMESH C.
S/O.CHIKKABAIYANNA AGED ABOUT 42 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
90. NEELAMMA W/O.NARAYANAPPA AGED ABOUT 50 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
91. PUSHPA G.
W/O.HARISH N.
AGED ABOUT 31 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
92. NANDHAN KUMAR H.G.
S/O.GOPALAPPA AGED ABOUT 28 YEARS HAROHALLI VILLAGE AND POST VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
93. HARISH N.
S/O.LATE NARAYANAPPA AGED ABOUT 44 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
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94. GOWTHAM M.
S/O.LATE MUNIKRISHNAPPA AGED ABOUT 21 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
95. SHANTHAMMA W/O.LATE MUNIKRISHNAPPA AGED ABOUT 49 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
96. RATHNAMMA D/O.MUNIYAPPA AGED ABOUT 41 YEARS BYRAPURA VILLAGE VIJAYAPURA HOBLI DEVANAHALLI TALUK BANGALORE RURAL DISTRICT-562 135
97. NAVEEN V.
S/O.VENKATESHAPPA AGED ABOUT 38 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
98. ASHWATHAPPA T.
S/O.A.ANNAPPA AGED ABOUT 52 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
99. T.N.NARAYANSWAMY S/O.NARAYANAPPA M. AGED ABOUT 58 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
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100. SWARNAMMA S/O.ASWATHAPPA AGED ABOUT 43 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
101. SAVITHA W/O.MURULIDHARA AGED ABOUT 32 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
102. ARPITHA D/O.VIJAYA KUMAR AGED ABOUT 23 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
103. GOWRAMMA W/O.AMBAREESH KUMAR AGED ABOUT 36 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
104. ARUNA R.
W/O.RAMAKRISHNAPPA AGED ABOUT 40 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
105. ASHWATHAPPA S/O.LATE ANNAPPA AGED ABOUT 51 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
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106. LALITHAMMA W/O.KEMPANNA AGED ABOUT 35 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
107. MANJULA W/O.BACHHEGOWDA AGED ABOUT 56 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
108. MUNIRAJU C.
S/O.CHOWDAPPA AGED ABOUT 61 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
109. SURESH R.
S/O.RAMANJINAPPA AGED ABOUT 36 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
110. VISHWANATH A.
S/O.AKKALAPPA AGED ABOUT 39 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
111. SONNEGOWDA T.A.
S/O.ANYAPPA AGED ABOUT 56 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
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112. MANJULA W/O.MUNIRAJU AGED ABOUT 37 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
113. T.N.BACHEGOWDA S/O.NARAYANAPPA T.C. AGED ABOUT 40 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
114. MUNIKRISHNA T.M.
S/O.T.S.MUNINARAYANAPPA AGED ABOUT 56 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
115. KRISHNAMURTHY T.H.
S/O.HANUMAPPA AGED ABOUT 63 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
116. PRASANNA A.
S/O.ASHWATHAPPA AGED ABOUT 36 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
117. MURULIDHARA S/O.NANJUNDAPPA AGED ABOUT 32 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
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118. BHAGYAMMA S/O.KRISHNAMURTHY AGED ABOUT 43 YEARS THIMMAHALLI VILLAGE BIJJAWARA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 110
119. NAGARAJU D.N.
S/O.CHIKKANANJUNDAPPA AGED ABOUT 43 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
120. MANASA MAHESH D/O.MAHESH AGED ABOUT 20 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
121. MUNIRAJA S/O.CHIKKANANJUNDAPPA AGED ABOUT 36 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
122. KAVITHA P.B.
S/O.CHANDREGOWDA AGED ABOUT 45 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
123. NARASAPPA S/O.DODDAVENKATESHAPPA AGED ABOUT 70 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
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124. RAGHU KUMAR S/O.LAKSHMINARAYANAPPA AGED ABOUT 36 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
125. UMESHA B.
S/O.BYRAPPA AGED ABOUT 52 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
126. NARAYANASWAMY S/O.SONNAPPA AGED ABOUT 56 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
127. BHARATHI K.
S/O.JANARDHAN M. AGED ABOUT 33 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
128. DEVARAJU D.M.
S/O.MUNIYAPPA AGED ABOUT 44 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
129. D.M.KESHAVAPPA S/O.MUNIYAPPA AGED ABOUT 43 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
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130. AJITH V.
S/O. BYREGOWDA AGED ABOUT 28 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
131. LAKSHMI S/O.KESHAVAPPA AGED ABOUT 36 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
132. D.V.PRAKASH KUMAR S/O.VENKATAPPA D.V. AGED ABOUT 41 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
133. SAVITHRI H.S.
W/O.SINNEGOWDA AGED ABOUT 33 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
134. MUNIRAMAPPA D.S.
S/O.SONNAPPA AGED ABOUT 48 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
135. PAVITHRA W/O.MUNIRAMAPPA D.S. AGED ABOUT 34 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
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136. D.MUNEGOWDA S/O.B.M.MUNINARAYANAPPA AGED ABOUT 49 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
137. SUJATHA R.
W/O.DEVARAJA D.M. AGED ABOUT 36 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
138. D.S.KRISHNAPPA S/O.DODDASUBBANNA AGED ABOUT 66 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
139. GOWRAMMA D.
S/O.S.KRISHNAPPA AGED ABOUT 56 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
140. NAGESH K.S.
S/O.KRISHNAPPA AGED ABOUT 35 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
141. PREMAMMA W/O.BYREGOWDA AGED ABOUT 46 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
- 25 -
142. VASANTHA KUMAR S/O.P.ANJANAPPA AGED ABOUT 36 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
143. JANARDHAN M.
S/O.MUNISWAMAPPA AGED ABOUT 45 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
144. MAHESHA D.A.
S/O.ANJINAPPA P. AGED ABOUT 32 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135
145. S.K.ROOPA S/O.VASANTHA KUMAR AGED ABOUT 33 YEARS DANADIGANAHALLI VIJAYAPURA POST VIJAYAPURA HOBLI BANGALORE RURAL-562 135 ... PETITIONERS (BY MS.MANASI SHARMA, ADVOCATE) AND:
1. KARNATAKA STATE POLLUTION CONTROL BOARD 'PARISARA BHAVAN' #49, CHURCH STREET BENGALURU-560 001 REP. BY ITS CHAIRMAN
2.  BY ITS CHAIRMAN/ MANAGING DIRECTOR ... RESPONDENTS (BY SHRI GURURAJ JOSHI, ADVOCATE FOR R1)
---
THESE WRIT PETITIONS ARE FILED UNDER ARTICLES 226 AND 227 OF THE CONSTITUTION OF INDIA, PRAYING TO SET ASIDE THE ORDER DATED 13.12.2017 (ANNEXURE-AM) OF THE SECOND RESPONDENT IN APPEAL NO.11/2017 AND ETC.
THESE PETITIONS COMING ON FOR PRELIMINARY HEARING THIS DAY, CHIEF JUSTICE MADE THE FOLLOWING:
ORDER Heard the learned counsel appearing for the petitioners.
2. The learned counsel appearing for the petitioners does not dispute that against the order dated 13th December 2017 passed by the Karnataka State Appellate Authority, an appeal is provided under clause(a) of Section 33-B of the Water (Prevention and Control of Pollution) Act, 1974.
However, she submits that the appellant was not heard by the Appellate Authority and the application for impleadment made
- 27 -
by the appellant is pending before the Appellate Authority, which is not being decided as the Appellate Authority is not properly constituted.
3. In view of the fact that an appeal provided against the impugned order lies before a body of experts like the National Green Tribunal and considering the facts of the case, we decline to entertain these writ petitions under Article 226 of the Constitution of India. The petitions are disposed of with liberty to the petitioners to prefer an appeal as aforesaid.
4. The National Green Tribunal may note the fact that the present petitions were filed on 3rd November 2018 and that the same remained pending till today.
Sd/-
CHIEF JUSTICE Sd/-
JUDGE LB


class: center, middle, inverse, title-slide # Lecture 02 ## Market Failures ### Ivan Rudik ### AEM 4510 --- exclude: true ```r if (!require("pacman")) install.packages("pacman") pacman::p_load( tidyverse, xaringanExtra, rlang, patchwork, nycflights13, tweetrmd, vembedr ) options(htmltools.dir.version = FALSE) knitr::opts_hooks$set(fig.callout = function(options) { if (options$fig.callout) { options$echo <- FALSE } knitr::opts_chunk$set(echo = TRUE, fig.align="center") options }) ``` ``` ## Warning: 'xaringanExtra::style_panelset' is deprecated. ## Use 'style_panelset_tabs' instead. ## See help("Deprecated") ``` ``` ## Warning in style_panelset_tabs(...): The arguments to `syle_panelset()` changed in xaringanExtra 0.1.0. Please ## refer to the documentation to update your slides. ``` --- # Roadmap - What are market failures? - When do they happen? - What are the consequences? --- class: inverse, center, middle name: what_is_enviro # Market failures and the environment

 --- # The ideal world In the best case scenario, a market equilibrium leads to the efficient allocation -- Example: bread -- We have a private bread supply curve (private MC) -- We have a private bread demand curve (private MB) -- In equilibrium: supply = demand so PMC = PMB = price -- For bread, the private costs and benefits are very likely the social costs and benefits --- # Market equilibrium .pull-left[ ![CS is area below demand, above price](02-slides-market-failures_files/figure-html/pmb-pmb-1.png) ] .pull-right[ .hi-red[Consumer surplus] is the difference between willingness to pay (demand) and price .hi-blue[Producer surplus] is the difference between price and marginal cost (supply) .hi[Total surplus] is the sum of CS and PS ] --- # Market equilibrium .pull-left[ ![CS is area below demand, above price](02-slides-market-failures_files/figure-html/pmb-pmb-1.png) ] .pull-right[ For bread, the private costs and benefits are very likely the social costs and benefits What does this mean about the market allocation? ] --- # Market equilibrium .pull-left[ ![CS is area below demand, above price](02-slides-market-failures_files/figure-html/pmb-pmb-1.png) ] .pull-right[ The market allocation is .hi-blue[efficient] because SMC = SMB Why? ] --- # Market equilibrium .pull-left[ ![CS is area below demand, above price](02-slides-market-failures_files/figure-html/pmb-pmb-1.png) ] .pull-right[ The market allocation is .hi-blue[efficient] because SMC = SMB Why? Consider deviating from `\((P^*, Q^*)\)` ] --- # Market equilibrium .pull-left[ ![CS is area below demand, above price](02-slides-market-failures_files/figure-html/pmb-pmb-1.png) ] .pull-right[ Cost of next unit after `\(Q^*\)` > benefit Benefit of last unit `\(\geq\)` cost of last unit before `\(Q^*\)` Competitive market allocations are efficient for private goods ] --- class: inverse, center, middle name: what_is_enviro # Externalities

 --- # Externalities If the world was just competitive markets, private goods, no third-parties, there would be no reason to do anything after Econ 101 -- That's not the case in the real world -- In the real world we have .hi-blue[externalities] > An externality exists whenever an individual or firm undertakes an action that impacts another individual or firm in an unintended way for which the latter is not compensated (a negative externality), or for which the latter does not pay (a positive externality) --- # Externalities What is problem with externalities for market outcomes and efficiency? -- There is not a market for the externality -- E.g. at Wegmans or Agway you will not find some important goods on sale: -- - Cleaner air outside -- - Biodiversity in the Amazon -- The central problem is that there are goods that are .hi-red[not priced], why is this a problem? -- Markets rely on prices to reflect value and have people make good decisions --- # Externalities: several classifications We can classify externalities in a few ways: -- .hi[Production externalities:] -- generated by a firm in the process of producing some output (e.g. pollution, innovation) -- .hi[Consumption externalities:] -- generated by an individual in the process of consuming an output (e.g. congestion, vaccination) -- .hi-red[Negative externalities:] -- imposes external **costs** (e.g. pollution) -- .hi-blue[Positive externalities:] -- imposes external **benefits** (e.g. vaccination) --- # Negative externalities: what is this?    --- # Negative externalities: DDT, shockingly bad for you .pull-left[  ] .pull-right[ DDT is a chemical that was was widely used as an insecticide in the early-mid 1900s Widely used to eradicate Typhus and Malaria Used to treat lice ] --- # Negative externalities: DDT, gives you cancer .pull-left[  ] .pull-right[ > A relationship between DDT exposure and reproductive effects in humans is suspected, based on studies in animals. In addition, some animals exposed to DDT in studies developed liver tumors. As a result, today, DDT is classified as a probable human carcinogen. ] --- # The birth of the environmental movement
--- # Negative externalities: graphical .pull-left[ ![externalities shift SMC up](02-slides-market-failures_files/figure-html/neg-ext0-1.png) ] .pull-right[ .hi-red[Social marginal cost (SMC)] is the sum of private marginal cost (PMC) and the external marginal cost (EMC) Where is the SMC? ] --- # Negative externalities: graphical .pull-left[ ![externalities shift SMC up](02-slides-market-failures_files/figure-html/neg-ext-1.png) ] .pull-right[ .hi-red[Social marginal cost (SMC)] is the sum of private marginal cost (PMC) and the external marginal cost (EMC) The PMC curve only reflects the **private costs** of making the DDT It does not account for the external health and wildlife costs ] --- # Negative externalities: graphical .pull-left[ ![externalities shift SMC up](02-slides-market-failures_files/figure-html/neg-ext-1.png) ] .pull-right[ Adding the private and external marginal costs together gives us the SMC, what we care about from the social planner or regulator's perspective ] --- # Negative externalities: graphical .pull-left[ ![externalities shift SMC up](02-slides-market-failures_files/figure-html/neg-ext-1.png) ] .pull-right[ Adding the private and external marginal costs together gives us the SMC, what we care about from the social planner or regulator's perspective The unregulated market gives us `\((P^u,Q^u)\)` as an outcome when we want `\((P^*,Q^*)\)` ] --- # Negative externalities: graphical .pull-left[ ![externalities shift SMC up](02-slides-market-failures_files/figure-html/neg-ext-1.png) ] .pull-right[ Adding the private and external marginal costs together gives us the SMC, what we care about from the social planner or regulator's perspective The unregulated market gives us `\((P^u,Q^u)\)` as an outcome when we want `\((P^*,Q^*)\)` What's the social cost of this market failure? ] --- # Negative externalities: graphical .pull-left[ ![externalities shift SMC up](02-slides-market-failures_files/figure-html/neg-ext-1.png) ] .pull-right[ Negative externalities generate deadweight loss equal to... ] --- # Negative externalities: graphical .pull-left[ ![externalities generate DWL](02-slides-market-failures_files/figure-html/neg-ext-dwl-1.png) ] .pull-right[ Negative externalities generate deadweight loss equal to the .hi-red[red] area ] --- # Negative externalities: graphical .pull-left[ ![externalities generate DWL](02-slides-market-failures_files/figure-html/neg-ext-dwl-1.png) ] .pull-right[ Negative externalities generate deadweight loss equal to the .hi-red[red] area This is the difference in SMC and SMB for units bought/sold where SMC > SMB: Total SMC - SMB from `\(Q^*\)` to `\(Q^u\)` ] --- # Negative externalities: graphical .pull-left[ ![externalities generate DWL](02-slides-market-failures_files/figure-html/neg-ext-dwl-1.png) ] .pull-right[ Negative externalities generate deadweight loss equal to the .hi-red[red] area This is the difference in SMC and SMB for units bought/sold where SMC > SMB This is the loss to society caused by the externality in the unregulated private market ] --- # Negative externalities: graphical .pull-left[ ![externalities generate DWL](02-slides-market-failures_files/figure-html/neg-ext-dwl-1.png) ] .pull-right[ Key takeaway: ] --- # Negative externalities: graphical .pull-left[ ![externalities generate DWL](02-slides-market-failures_files/figure-html/neg-ext-dwl-1.png) ] .pull-right[ Key takeaway: The private market produces too much DDT ] --- # Negative externalities: graphical .pull-left[ ![externalities generate DWL](02-slides-market-failures_files/figure-html/neg-ext-dwl-1.png) ] .pull-right[ Key takeaway: The private market produces too much DDT The private actors are not accounting for the .hi[external costs] they are imposing on people who are not in the DDT transaction (e.g. third parties whose health is being affected) ] --- # Estimating marginal damages with EZ-Pass
--- # Positive externalities    --- # Positive externalities .pull-left[  ] .pull-right[ Vaccines and masks are examples of good with positive externalities You getting or using them has benefits for other people not involved in your vaccine or mask transaction ] --- # Positive externalities: graphical .pull-left[ ![externalities shift SMB up](02-slides-market-failures_files/figure-html/pos-ext0-1.png) ] .pull-right[ .hi-red[Social marginal benefit (SMB)] is the sum of private marginal benefit (PMB) and the external marginal benefit (EMB) Where does the SMB curve lie? ] --- # Positive externalities: graphical .pull-left[ ![externalities shift SMB up](02-slides-market-failures_files/figure-html/pos-ext-1.png) ] .pull-right[ .hi-red[Social marginal benefit (SMB)] is the sum of private marginal benefit (PMB) and the external marginal benefit (EMB) ] --- # Positive externalities: graphical .pull-left[ ![externalities shift SMB up](02-slides-market-failures_files/figure-html/pos-ext-1.png) ] .pull-right[ .hi-red[Social marginal benefit (SMB)] is the sum of private marginal benefit (PMB) and the external marginal benefit (EMB) The PMB curve only reflects the **private benefits** of getting a vaccine ] --- # Positive externalities: graphical .pull-left[ ![externalities shift SMB up](02-slides-market-failures_files/figure-html/pos-ext-1.png) ] .pull-right[ .hi-red[Social marginal benefit (SMB)] is the sum of private marginal benefit (PMB) and the external marginal benefit (EMB) The PMB curve only reflects the **private benefits** of getting a vaccine It does not account for the external herd immunity benefits ] --- # Positive externalities: graphical .pull-left[ ![externalities shift SMB up](02-slides-market-failures_files/figure-html/pos-ext-1.png) ] .pull-right[ Adding the private and external marginal benefits together gives us the SMB, what we care about from the social planner or regulator's perspective ] --- # Positive externalities: graphical .pull-left[ ![externalities shift SMB up](02-slides-market-failures_files/figure-html/pos-ext-1.png) ] .pull-right[ Adding the private and external marginal benefits together gives us the SMB, what we care about from the social planner or regulator's perspective The unregulated market gives us `\((P^u,Q^u)\)` as an outcome when we want `\((P^*,Q^*)\)` ] --- # Positive externalities: graphical .pull-left[ ![externalities shift SMB up](02-slides-market-failures_files/figure-html/pos-ext-1.png) ] .pull-right[ Adding the private and external marginal benefits together gives us the SMB, what we care about from the social planner or regulator's perspective The unregulated market gives us `\((P^u,Q^u)\)` as an outcome when we want `\((P^*,Q^*)\)` What's the social cost of this market failure? ] --- # Positive externalities: graphical .pull-left[ ![externalities shift SMB up](02-slides-market-failures_files/figure-html/pos-ext-1.png) ] .pull-right[ Positive externalities generate deadweight loss equal to... ] --- # Positive externalities: graphical .pull-left[ ![pos externalities generate DWL](02-slides-market-failures_files/figure-html/pos-ext-dwl-1.png) ] .pull-right[ Positive externalities generate deadweight loss equal to the .hi-blue[blue] area ] --- # Positive externalities: graphical .pull-left[ ![pos externalities generate DWL](02-slides-market-failures_files/figure-html/pos-ext-dwl-1.png) ] .pull-right[ Positive externalities generate deadweight loss equal to the .hi-blue[blue] area This is the difference in SMB and SMC for units where SMC < SMB: Total SMB - SMC from `\(Q^u\)` to `\(Q^*\)` ] --- # Positive externalities: graphical .pull-left[ ![pos externalities generate DWL](02-slides-market-failures_files/figure-html/pos-ext-dwl-1.png) ] .pull-right[ Positive externalities generate deadweight loss equal to the .hi-blue[blue] area This is the difference in SMB and SMC for units where SMC < SMB This is the loss to society caused by the externality in the unregulated private market ] --- # Positive externalities: graphical .pull-left[ ![pos externalities generate DWL](02-slides-market-failures_files/figure-html/pos-ext-dwl-1.png) ] .pull-right[ The private market produces too few vaccines The private actors are not accounting for the social benefits they are imposing on people who are not in the vaccine transaction (e.g. third parties whose health is being affected) ] --- # COVID and positive externalities
--- # COVID and positive externalities
--- # Why do externalities arise? Typically one of two reasons: -- 1. Poorly defined property rights - Who owns the right to the air? -- 2. High transactions costs - Hard to bargain over desired air quality with millions of people Lets conceptualize a model of efficient bargaining using an Edgeworth Box --- # Why do externalities arise? Edgeworth Box - Two individuals: A and B - Two private goods: X and Y Each individual begins with an initial endowment of each good: - `\(A: w_X^A, w_Y^A\)` - `\(B: w_X^B, w_Y^B\)` This gives us a total endowment: - `\(W_X = w_X^A + w_X^B\)` - `\(W_Y = w_Y^A + w_Y^B\)` --- # Why do externalities arise? Edgeworth Box    --- # Why do externalities arise? Edgeworth Box .pull-left[    ] .pull-right[ Total vertical distance is `\(W_Y\)` Total horizontal distance is `\(W_X\)` Initial endowment is given by the empty circle Initial indifference curves for A and B are `\(UA(0)\)` and `\(UB(0)\)` ] --- # Why do externalities arise? Edgeworth Box .pull-left[    ] .pull-right[ Is there a possible Pareto improvement? e.g. can we make both A and B better off? ] --- # Why do externalities arise? Edgeworth Box .pull-left[    ] .pull-right[ Yes! ] --- # Why do externalities arise? Edgeworth Box .pull-left[    ] .pull-right[ Yes! If we move anywhere in the lens of their initial indifference curves we have a Pareto improvement If we move to an allocation where their indifference curves are .hi[tangent] to one another (e.g. the filled-in point), we have a Pareto optimum ] --- # Why do externalities arise? Edgeworth Box In a properly functioning market: - The endowment point is well-established -- - A and B can trade X and Y to some Pareto improving point -- - They continue trading until they achieve a Pareto optimal allocation -- - This allocation lies on the .hi[contract curve]: the line consisting of all Pareto efficient allocations --- # Why do externalities arise? Edgeworth Box    --- # Why do externalities arise? Edgeworth Box Now suppose Y is not a private good, but a public good/bad, e.g. smoke -- This means that A and B consume the .hi[exact same level of Y] -- Unlike our regular Edgeworth Box, now Y increases for .hi[both] A and B as we move to the top of the slide (before Y increased for B as we moved to the bottom) -- Suppose that A likes Y, but B does not -- Suppose both start off with the same quantity of X --- # Why do externalities arise? Edgeworth Box .pull-left[    ] .pull-right[ Depending on who has property rights, we either start at: - W1 (B has property rights) - W2 (A has property rights) Think about why these are where we must start ] --- # Why do externalities arise? Edgeworth Box .pull-left[    ] .pull-right[ Suppose we start at W1, what happens? ] --- # Why do externalities arise? Edgeworth Box .pull-left[    ] .pull-right[ Suppose we start at W1, what happens? A wants to have more Y, but this imposes a cost on B ] --- # Why do externalities arise? Edgeworth Box .pull-left[    ] .pull-right[ Suppose we start at W1, what happens? A wants to have more Y, but this imposes a cost on B Therefore, A has to .hi[pay] B to get more Y ] --- # Why do externalities arise? Edgeworth Box .pull-left[    ] .pull-right[ Suppose we start at W1, what happens? A wants to have more Y, but this imposes a cost on B Therefore, A has to .hi[pay] B to get more Y A pays B in units of X, move to Z1, Pareto optimum ] --- # Why do externalities arise? Edgeworth Box .pull-left[    ] .pull-right[ Suppose we start at W2, what happens? ] --- # Why do externalities arise? Edgeworth Box .pull-left[    ] .pull-right[ Suppose we start at W2, what happens? B wants to have less Y, but this imposes a cost on A ] --- # Why do externalities arise? Edgeworth Box .pull-left[    ] .pull-right[ Suppose we start at W2, what happens? B wants to have less Y, but this imposes a cost on A Therefore, B has to .hi[pay] A to get less Y ] --- # Why do externalities arise? Edgeworth Box .pull-left[    ] .pull-right[ Suppose we start at W2, what happens? B wants to have less Y, but this imposes a cost on A Therefore, B has to .hi[pay] A to get less Y B pays A in units of X, move to Z2, Pareto optimum ] --- # Why do externalities arise? Edgeworth Box In the previous example we were able to achieve the Pareto optimum even with a public good / externality -- Why? -- 1. Property rights were assigned to either A or B -- 2. Transactions costs were low (didn't have to pay a fee to trade X) --- # Property rights and externalities A solution to many externalities is to just assign property rights and let the market do its thing -- We'll talk about a few ways that we can assign property rights --- # Transactions costs and externalities Now suppose there were many non-smokers -- Even if they were assigned the property rights, it might be hard for them to bargain - Takes a lot of time to find something that works for everyone - Negotiating over how much X each person gets -- The costs of bargaining may exceed the benefits and we end up stuck at W2 --- # Transactions costs and externalities Road noise: drivers implicitly have property rights to noise around roads -- Even if you prefer quiet, you can't negotiate a payment with every loud car that might pass pay --- # The free-rider problem Externalities and public goods/bads often exhibit many of the same features Both are subject to the .hi[Free-Rider Problem] > A type of market failure that occurs when those who benefit from resources, public goods (such as public roads or hospitals), or services of a communal nature do not pay for them[1] or under-pay e.g. - people don't pay their taxes for publicly-provided services - non-smokers will wait for others to pay in order to reduce smoke --- class: inverse, center, middle name: what_is_enviro # The provision of public goods

 --- # Public goods How do we efficiently provide public goods? We know: - Private goods: PMB = PMC `\(\leftrightarrow\)` SMB = SMC - Goods with negative externalities: PMB = SMC `\(\leftrightarrow\)` SMB = SMC - goods with positive externalities: SMB = PMC `\(\leftrightarrow\)` SMB = SMC -- Suppose we have a public good, e.g. depth of a river for public use How do we decide the socially efficient depth? --- # Public goods Optimal provision is .hi-blue[always] given by: SMB = SMC What are the SMB and SMC for a public good? -- Think about the characteristics of a public good, one of them is critical: -- .hi[Non-rival:] multiple people can use the same unit of a good (one person using the river doesn't 'use up' its depth) -- This means multiple people can derive benefits from the provision of 1 unit of the good --- # Optimal provision of public goods What does this mean? -- When we count up the SMB, we need to add up .hi-blue[everyone's] PMB: .hi[Optimality:] `\(SMB = \sum_i PMB_i = PMC\)` -- If we ignore the fact that public goods are non-rival, we get underprovision of the good -- e.g. the free market underprovides clean air, national defense, etc --- # Modeling the provision of public goods How do we model public goods? -- First: how do we aggregate marginal benefit or demand curves? Here's how to think about it: -- .hi-blue[For private goods:] -- Private goods are rival, only one person can consume each unit -- At each price, what is the total quantity that is demanded? -- At each price, we need to add up quantities -- Private goods: we add demand curves horizontally --- # Modeling the provision of public goods .hi-blue[For public goods:] -- Public goods are non-rival, multiple people can consume each unit -- At each quantity, what is the total marginal benefit? -- At each quantity, we need to add up PMBs/prices -- Public goods: we add demand curves vertically --- # Public goods: graphical .pull-left[ ![public good demand curves](02-slides-market-failures_files/figure-html/pub-good-1.png) ] .pull-right[ 3 different groups: boaters (B), anglers (A), and hikers (H) Each has a different marginal benefit for water depth: - Boaters: MB = 12-Q - Anglers: MB = 10-Q - Hikers: MB = 6-Q - MC of provision: MC = Q ] --- # Public goods: graphical .pull-left[ ![aggregate public good demand](02-slides-market-failures_files/figure-html/pub-good-agg-1.png) ] .pull-right[ Now we need to aggregate them to get the .hi[social marginal benefit] We do so by adding up the demand curves vertically: At each Q, sum the MBs ] --- # Public goods: graphical .pull-left[ ![aggregate public good demand](02-slides-market-failures_files/figure-html/pub-good-agg-1.png) ] .pull-right[ Why is the aggregate demand curve kinked? Because at each quantity/depth, only certain groups are willing to use the river Kinks are at the dotted lines, where PMBs hit zero ] --- # Positive externalities: graphical .pull-left[ ![aggregate public good demand](02-slides-market-failures_files/figure-html/pub-good-agg-1.png) ] .pull-right[ At quantities > 10, only boaters are willing to pay At quantities > 6 and <= 10, only boaters and anglers are willing to pay At quantities =< 6 all groups are willing to pay to use the river ] --- # Positive externalities: graphical .pull-left[ ![aggregate public good demand](02-slides-market-failures_files/figure-html/pub-good-agg-1.png) ] .pull-right[ The SMB curve is: 28 - 3Q for Q <= 6 22 - 2Q for 6 < Q <= 10 12 - Q for 10 < Q <= 12 Summing the PMBs over the relevant range of Q ] --- # Public goods: graphical .pull-left[ ![aggregate public good demand](02-slides-market-failures_files/figure-html/pub-good-optim-1.png) ] .pull-right[ The optimal provision of the public good is where the MC curve crosses the SMB curve This is across the middle segment Q = 22 - 2Q `\(\Rightarrow\)` Q = 22/3 The optimal quantity of Q = 22/3 is greater than the quantity any individual group would be willing to purchase ] --- # Public goods financing The socially optimal quantity is greater than the individual privately optimal quantities -- This means that the MC of provision, MC = 22/3 -- Is this the price the groups pay? -- .hi[No!] It is greater than any individual group is willing to pay -- If the government is able to provide the good, how does it finance the cost raising the river depth above zero? --- # Public goods financing It charges each group a share of this price -- What share is everyone charged? -- .hi[Lindahl pricing:] charge each group equal to their marginal benefit -- Boaters pay: 14/3 Anglers pay: 8/3 Hikers: free -- Notice that the prices sum to the marginal cost! -- Since the good is non-rival, this is enough to finance the cost --- # Public goods financing What is a key problem with Lindahl pricing? -- People can lie about which group they're in -- Anglers might say they're hikers -- It requires perfect information on behalf of the regulator


{% extends 'base.html' %} {% load i18n %} {% block content %}
{% trans "You have been logged out of City of Helsinki services." %}
{% if backend and backend.user_facing_url %}{% blocktrans trimmed with name_logged_in=backend.name_logged_in_to %} Please note that you are still logged in to {{ name_logged_in }}, whose credentials you originally used to log in to City of Helsinki services. {% endblocktrans %}
{% blocktrans trimmed with name_access=backend.name_access name_logout=backend.name_logout_from %} If access to this device is shared by other users, the next user will be able to access your {{ name_access }} account unless you explicitly log out from {{ name_logout }}. {% endblocktrans %}
{% blocktrans trimmed with name_goto=backend.name_goto name_genetive=backend.name_genetive url=backend.user_facing_url%} Go back to {{ name_goto }} to log yourself out using {{ name_genetive }} own logout feature. {% endblocktrans %}
{% blocktrans trimmed with name_goto=backend.name_goto %} Go to {{ name_goto }} {% endblocktrans %}


The representation of associations between two classes of features becomes
complex when the number in each class increases and this occurs for instance
when investigating:
genes to clinical parameters.
mRNA to miRNA.
subjects to lifestyles.
Heatmap is a regular proposition, but can be confusing, and it should be
carefully designed so as to help identifying the most relevant associations
between individual features or group of features. In the example below:
The association between a row feature and a column feature is quantified at
the intersection.
The intensity of the shade corresponds to the absolute value of the
correlation.
We should always understand the rational for row or column ordering:
in that case, an unsupervised hierarchical classification was applied;
within rows (or columns) to close features (distance derived from correlation)
will be found grouped together. The information is supported by the addition
of the dendrogram in the margins.
The numbers are the correlations; number by themselves may not
be of main interest so the first visible information is actually
the colour of the numbers corresponding to the discrimination of significance
(yellow, p.value < 0.5; green otherwise). Still, looking closer at the
matrix give access to the actual correlation value if required (e.g. for
reporting).
From that, we understand that the rows and columns features under the
magnifier glass constitute two groups which association support their
identification as good candidates to push the analysis further.


REPUBLIC OF TURKEY
INTENDED NATIONALLY DETERMINED CONTRIBUTION
In accordance with decisions 1/CP.19 and 1/CP.20, the Republic of Turkey hereby presents its Intended Nationally Determined Contribution (INDC) towards achieving the ultimate objective of the United Nations Framework Convention on Climate Change which is set out in its Article 2 and clarifying information.
National Circumstances
Turkey achieved 230 per cent increase in GDP between 1990 and 2012. Its population has increased more than 30 per cent since 1990. Turkey’s energy demand increases by 6-7 percent every year.
Turkey is an upper-middle income developing country according to the World Bank classification. Turkey remains eligible to official development assistance (ODA).
Turkey is listed in Annex I to the UNFCCC. However, Decision 1/CP.16 recognized the special circumstances of Turkey and placed Turkey in a different situation than the other Parties included in Annex I.
Turkey aims to contribute to the collective efforts to combat climate change in line with its national circumstances and capabilities.
With this perspective, National Strategy on Climate Change and National Climate Change Action Plan were adopted in 2010 and 2011 respectively.
National Climate Change Action Plan consists of emission control and adaptation policies and measures which are being implemented in all relevant sectors.
The greenhouse gas inventory of the year 2012 revealed that the total emissions in 2012 expressed in CO2 equivalent were 440 million tons in Turkey. The energy sector had the largest share with 70.2 percent. Industrial processes with 14.3 percent, waste sector with 8.2 percent and agriculture with 7.3 percent followed the energy sector. Turkey’s per capita greenhouse gas (GHG) emission for the same year was 5.9 ton CO2 equivalent, which is much lower than the EU and OECD average.
Information on INDC
INDC
Up to 21 percent reduction in GHG emissions from the Business as Usual (BAU) level by 2030.
Period for Implementation or Contribution
2021-2030
Scope and Coverage
Economy-wide.
Energy, industrial processes and products use, agriculture, land use
land-use change and forestry, and waste sectors.
GHGs
All greenhouse gases included in the national inventory:
- Carbon dioxide (СО2);
- Methane (СН4);
- Nitrous oxide (N2O);
- Hydrofluorocarbons (HFCs);
- Perfluorocarbons (PFCs);
- Sulfur hexafluoride (SF6);
- Nitrous trifluoride (NF3).
Methodological approaches
Methodological approaches are based on using the IPCC 2006 Guidelines and IPCC 2013 KP Supplement.
Global warming potential on a 100 year timescale in accordance with the IPCC’s 4th Assessment Report.
Use of International Market Mechanisms
Turkey aims to use carbon credits from international market mechanisms to achieve its 2030 mitigation target in a cost effective manner and in accordance with the relevant rules and standards.
Consideration of fairness and ambition based on national conditions
Turkey has to continue its sustainable development process.
Rapid industrialization and urbanization have been taking place in Turkey over the last 30 years.
Turkey is responsible for only 0.7 percent of the global emissions since the industrial revolution.
Energy imports have a significant share in Turkey’s account deficit. Turkey has to use its limited energy resources.
Turkey experiences financial and technological constraints in combating climate change.
This INDC provides additional policies, plans and measures in many sectors.
How the INDC contributes to achieving the ultimate objective of the Convention (Article 2)
Up to 21 percent reduction in GHG emissions from the BAU level by 2030 will enable Turkey to step on low-carbon development pathways compatible with the long-term objective of limiting the increase in global temperature below 2°C.
Planning Process
Turkey may revise this INDC in accordance with changing circumstances.
Turkey supports its INDC through a national climate change policy which includes;
- 10th National Development Plan
- National Strategy on Climate Change
- National Climate Change Action Plan
- National Strategy on Industry
- Strategy on Energy Efficiency
- National Strategy and Action Plan on Recycling
- National Legislation on Monitoring, Reporting and Verification of GHG emissions
- National Smart Transportation Systems Strategy Document (2014-2023) and its Action Plan (2014-2016)
Turkey’s INDC was prepared in a participatory approach through multiple stakeholder meetings and by analytical studies conducted for 1 year.
Times-MACRO model is used for energy related modeling and other national models and studies are used for non-energy sectors.
Financial Needs
Recalling the decisions 26/CP.7, 1/CP.16, 2/CP.17, 1/CP.18 and 21/CP.20, in view of successfully implementing this INDC, Turkey will use domestic sources and receive international financial, technological, technical and capacity building support, including finance from the Green Climate Fund.
Plans and policies to be implemented for this INDC
Energy
- Increasing capacity of production of electricity from solar power to 10 GW until 2030
- Increasing capacity of production of electricity from wind power to 16 GW until 2030
- Tapping the full hydroelectric potential
- Commissioning of a nuclear power plant until 2030
- Reducing electricity transmission and distribution losses to 15 percent at 2030
- Rehabilitation of public electricity generation power plants
- Establishment of micro-generation, co-generation systems and production on site at electricity production
Industry
- Reducing emission intensity with the implementation of National Strategy and Action Plan on Energy Efficiency
- Increasing energy efficiency in industrial installations and providing financial support to energy efficiency projects
- Making studies to increase use of waste as an alternative fuel at the appropriate sectors
Transport
- Ensuring balanced utilization of transport modes in freight and passenger transport by reducing the share of road transport and increasing the share of maritime and rail transport
- Enhancing combined transport
- Implementing sustainable transport approaches in urban areas
- Promoting alternative fuels and clean vehicles
- Reducing fuel consumption and emissions of road transport with National Intelligent Transport Systems Strategy Document (2014-2023) and its Action Plan (2014-2016)
- Realizing high speed railway projects
- Increasing urban railway systems
- Achieving fuel savings by tunnel projects
- Scraping of old vehicles from traffic
- Implementing green port and green airport projects to ensure energy efficiency
- Implementing special consumption tax exemptions for maritime transport
Buildings and Urban Transformation
- Constructing new residential buildings and service buildings as energy efficient in accordance with the Energy Performance of Buildings Regulations
- Creating Energy Performance Certificates for new and existing buildings so as to control energy consumption and greenhouse gas emissions and to reduce energy consumption per square meter
- Reducing the consumption of primary energy sources of new and existing buildings by means of design, technological equipment, building materials, development of channels that promote the use of renewable energy sources (loans, tax reduction, etc.)
- Dissemination of Green Building, passive energy, zero-energy house design in order to minimize the energy demand and to ensure local production of energy
Agriculture
- Fuel savings by land consolidation in agricultural areas
- Rehabilitation of grazing lands
- Controlling the use of fertilizers and implementing modern agricultural practices
- Supporting the minimum tillage methods
Waste
- Sending solid wastes to managed landfill sites
- Reuse, recycle and use of other processes to recover secondary raw materials, to utilize as energy source or to remove wastes
- Recovering energy from waste by using processes such as material recycling of wastes, bio-drying, bio-methanization, composting, advanced thermal processes or incineration
- Recovery of methane gas from landfill gas from managed and unmanaged landfill sites
- Utilization of industrial wastes as an alternative raw material or alternative fuel in other industrial sectors, through industrial symbiosis approach
- Conducting relevant studies to utilize wastes generated from breeding farms and poultry farms
- Rehabilitation of unmanaged waste sites and ensuring wastes to be deposited at managed landfill sites.
Forestry
- Increasing sink areas and preventing land degradation
- Implementing Action Plan on Forestry Rehabilitation and National Afforestation Campaign
The emission reductions to be achieved by these policies and plans compared to the business-as-usual scenario are presented in the figure below.


| 012:063 Khan | : |
So, when they returned to their father, they said: "O our father! No more measure of grain shall we get (unless we take our brother). So send our brother with us, and we shall get our measure and truly we will guard him." |
| 012:063 Maulana | : |
So when they returned to their father, they said: O our father, the measure is withheld from us, so send with us our brother that we may get the measure, and we will surely guard him. |
| 012:063 Pickthal | : |
So when they went back to their father they said: O our father! The measure is denied us, so send with us our brother that we may obtain the measure, surely we will guard him well. |
| 012:063 Rashad | : |
When they returned to their father, they said, "Our father, we can no longer get any provisions, unless you send our brother with us. We will take good care of him." |
| 012:063 Sarwar | : |
When they returned to their father, they told him, "Father, (unless we take our brother) they will refuse us one further measure of grain. Send our brother with us so that we can obtain that measure. We shall watch over him carefully". |
| 012:063 Shakir | : |
So when they returned to their father, they said: O our father, the measure is withheld from us, therefore send with us our brother, (so that) we may get the measure, and we will most surely guard him. |
| 012:063 Sherali | : |
And when they returned to their father, they said, 'O our father, any further measure of corn has been denied us, so send with us our brother that we may obtain our measure, and we will surely be able to take care of him.' |
| 012:063 Yusufali | : |
Now when they returned to their father, they said: "O our father! No more measure of grain shall we get (unless we take our brother): So send our brother with us, that we may get our measure; and we will indeed take every care of him." |
Concepts/Themes Covered: القصص والتاريخ > يعقوب The Stories and the History>Jacob
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


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6
Data management routines
6.1
psb_cdall — Allocates a communication descriptor
6.2
psb_cdins — Communication descriptor insert routine
6.3
psb_cdasb — Communication descriptor assembly routine
6.4
psb_cdcpy — Copies a communication descriptor
6.5
psb_cdfree — Frees a communication descriptor
6.6
psb_cdbldext — Build an extended communication descriptor
6.7
psb_spall — Allocates a sparse matrix
6.8
psb_spins — Insert a set of coefficients into a sparse matrix
6.9
psb_spasb — Sparse matrix assembly routine
6.10
psb_spfree — Frees a sparse matrix
6.11
psb_sprn — Reinit sparse matrix structure for psblas routines.
6.12
psb_geall — Allocates a dense matrix
6.13
psb_geins — Dense matrix insertion routine
6.14
psb_geasb — Assembly a dense matrix
6.15
psb_gefree — Frees a dense matrix
6.16
psb_gelp — Applies a left permutation to a dense matrix
6.17
psb_glob_to_loc — Global to local indices convertion
6.18
psb_loc_to_glob — Local to global indices conversion
6.19
psb_is_owned —
6.20
psb_owned_index —
6.21
psb_is_local —
6.22
psb_local_index —
6.23
psb_get_boundary — Extract list of boundary elements
6.24
psb_get_overlap — Extract list of overlap elements
6.25
psb_sp_getrow — Extract row(s) from a sparse matrix
6.26
psb_sizeof — Memory occupation
6.27
Sorting utilities —
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UI NeuroRepository
The UI Neurorepository was established to provide a network of resources to integrate human neurological disease specific clinical, electrophysiological, histopathological, imaging, and molecular data; linking molecular information to disease processes in order to generate new research directions. The UI Neurorepository enables investigators to identify both targets and biomarkers through a unique biorepository that is clinically and anatomically linked to a human subject data repository. The incorporation of radiological and microscopic images, as well as electrical records that are directly linked to each piece of human brain and other tissues provides a basis for discovery not available through any other tissue bank or data warehouse.
The UI Neurorepository serves investigators from multiple disciplines, including but not limited to neurology, neurosurgery, psychiatry, neuroscience, neuroimaging, and computational neuroscience. Our current collection includes thousands of neocortical brain samples from patients undergoing epilepsy surgery where each piece of tissue is linked to imaging, in vivo electrical recordings, and an extensive clinical database. Studies from this collection have led to multiple important discoveries on the abnormal wiring of the epileptic brain, molecular pathways involved, novel therapeutic targets, and biomarkers. A second disease is ALS where we collect rapid postmortem autopsy tissues that are directly linked to clinical disease progression.
Additional information may be found at the UIC Department of Neurology.


R/rvtable.R
Class constructor for rvtable
objects.
rvtable(x, y = NULL, Val, Prob, discrete = FALSE, density.args = list(), weights = list(), force.dist = TRUE)
| x | a numeric vector or data frame. |
|---|---|
| y | an optional vector of probabilities associated with |
| Val | the column name of |
| Prob | the column name of |
| discrete | whether the random variable is discrete. |
| density.args | optional arguments passed to |
| weights |
|
| force.dist | logical, force distribution-type rvtable output if |
an object of class rvtable
.
These are long format data tables containing a Val and Prob column describing the distribution of a random variable.
Any other columns are ID columns and should be categorical variables. The random variable described by Val and Prob may be discrete or continuous.
When discrete, probabilities are true probabilities.
When continuous, Val and Prob are based on x
and y
output from density
and describe a distribution curve,
and therefore values in Prob may be greater than one and may not sum to one.
Val is typically numeric but may be character when discrete such as when an rvtable object is returned from inverse_pmf
.
For data frame inputs, Val and Prob here refer generally to whatever columns in an rvtable are specified by Val
and Prob
.
In rvtable
, if the Val
argument is not supplied, Val is assumed to be Val="Val"
and rvtable
will search the names of a data frame for this column, throwing an error if it is not found, like with any other value of Val
.
When Prob
is missing, however, this is analogous to when x
is numeric and
y
and x
probability attributes are both NULL: the data in the Val
column are assumed to be a direct sample
from a distribution rather than a vector of values that describes a distribution in conjunction with a Prob
column.
When x
is numeric, a supplied Val
will substitute for rvtable names x
and y
in the output, respectively.
All rvtable objects are in one of two forms: distribution-type or sample-type.
This primary constructor constructs distribution- or sample-type rvtable objects,
with the corresponding attribute tabletype="distribution"
or tabletype="sample"
.
Sampling on an rvtable can generate a sample-type rvtable, with the attribute tabletype="sample"
.
Other operations like merging or marginalizing distributions typically yield rvtables in distribution form.
This is the common form and rvtables are usually kept in this form until a final step in a processing chain
where samples are needed.
Every rvtable object also has a variable type attribute, rvtype
, which is either "discrete" or "continuous".
Other attributes assigned during rvtable construction include valcol
and probcol
, the names of the Val and Prob columns,
and a density.args
attribute that lists any most recent arguments passed to density
in the process
of making the rvtable.
If an rvtable is already of class rvtable
, the rvtable
function simply returns
the rvtable as is; any other arguments passed to rvtable
are ignored and
neither the table nor its attributes are updated or altered in any way.
Weights for levels of an ID variable are can be set by set_weights
.
In rvtable
, weights
is passed to set_weights
so that weights can be set on rvtable construction if desired.
It can be relatively cumbersome to set weights for all ID variables at once in a call to rvtable
, and
particularly wasteful if there are several ID columns and most or all have levels with equal weights.
The weights attribute assigned to the rvtable will be an empty list
if there are no ID columns in x
and a named list of data frames otherwise.
The names are the names of the ID variables in x
and each data frame has two columns: levels
and weights
,
giving the weighting of an ID variable's levels.
When weights=NULL
or weights=list()
, the values in the weights
column for each level in each data frame
are set to 1
for equal weighting.
Similarly, individual named list elements can be set to NULL
for convenience instead of passing a data frame.
NULL
or list()
elements in the weights
list are converted to data frames with weights equal to one.
Note that weights
is ignored if x
is not a data frame.
# basic samples from continuous and discrete RVs x <- rnorm(100) rvtable(x)#> # A tibble: 512 x 2 #> x y #> <dbl> <dbl> #> 1 -3.45 0.000213 #> 2 -3.44 0.000240 #> 3 -3.42 0.000269 #> 4 -3.41 0.000302 #> 5 -3.39 0.000339 #> 6 -3.38 0.000379 #> 7 -3.36 0.000424 #> 8 -3.34 0.000474 #> 9 -3.33 0.000528 #> 10 -3.31 0.000588 #> # ... with 502 more rowsrvtable(x, density.args=list(n=50, adjust=2))#> # A tibble: 50 x 2 #> x y #> <dbl> <dbl> #> 1 -4.73 0.000191 #> 2 -4.52 0.000428 #> 3 -4.30 0.000906 #> 4 -4.08 0.00181 #> 5 -3.86 0.00342 #> 6 -3.64 0.00614 #> 7 -3.43 0.0104 #> 8 -3.21 0.0169 #> 9 -2.99 0.0261 #> 10 -2.77 0.0385 #> # ... with 40 more rowsrvtable(x, discrete=TRUE) # incorrect: x is a continuous RV#> # A tibble: 100 x 2 #> x y #> <dbl> <dbl> #> 1 -2.18 0.0100 #> 2 -2.12 0.0100 #> 3 -1.87 0.0100 #> 4 -1.87 0.0100 #> 5 -1.85 0.0100 #> 6 -1.80 0.0100 #> 7 -1.78 0.0100 #> 8 -1.64 0.0100 #> 9 -1.47 0.0100 #> 10 -1.43 0.0100 #> # ... with 90 more rowsx <- sample(1:10, size=30, replace=TRUE, prob=sqrt(10:1)) rvtable(x, discrete=TRUE) # discrete=T only needed if ambiguous#> # A tibble: 9 x 2 #> x y #> <dbl> <dbl> #> 1 1.00 0.167 #> 2 2.00 0.100 #> 3 3.00 0.133 #> 4 4.00 0.0333 #> 5 5.00 0.167 #> 6 6.00 0.133 #> 7 7.00 0.133 #> 8 8.00 0.0667 #> 9 9.00 0.0667x <- 1:5 probs <- c(0.1, 0.2, 0.3, 0.15, 0.25) rvtable(x, y=probs) # discrete inferred from y#> # A tibble: 5 x 2 #> x y #> <int> <dbl> #> 1 1 0.100 #> 2 2 0.200 #> 3 3 0.300 #> 4 4 0.150 #> 5 5 0.250attr(x, "probabilities") <- probs rvtable(x) # inferred from attributes (partial match 'prob')#> # A tibble: 5 x 2 #> x y #> <int> <dbl> #> 1 1 0.100 #> 2 2 0.200 #> 3 3 0.300 #> 4 4 0.150 #> 5 5 0.250# an existing data frame or data table x <- data.frame(Val=1:10, Prob=0.1) rvtable(x)#> # A tibble: 10 x 2 #> Val Prob #> <int> <dbl> #> 1 1 0.100 #> 2 2 0.100 #> 3 3 0.100 #> 4 4 0.100 #> 5 5 0.100 #> 6 6 0.100 #> 7 7 0.100 #> 8 8 0.100 #> 9 9 0.100 #> 10 10 0.100x <- data.frame(id=rep(LETTERS[1:2], each=10), v1=rep(1:10, 2), p1=c(rep(0.1, 10), sqrt(1:10))) rvtable(x, Val="v1", Prob="p1")#> # A tibble: 20 x 3 #> id v1 p1 #> <fct> <int> <dbl> #> 1 A 1 0.100 #> 2 A 2 0.100 #> 3 A 3 0.100 #> 4 A 4 0.100 #> 5 A 5 0.100 #> 6 A 6 0.100 #> 7 A 7 0.100 #> 8 A 8 0.100 #> 9 A 9 0.100 #> 10 A 10 0.100 #> 11 B 1 1.00 #> 12 B 2 1.41 #> 13 B 3 1.73 #> 14 B 4 2.00 #> 15 B 5 2.24 #> 16 B 6 2.45 #> 17 B 7 2.65 #> 18 B 8 2.83 #> 19 B 9 3.00 #> 20 B 10 3.16


# File spec/test_data/rb_omission.rb, line 5 5: def test_data 6: "rb omission" 7: end
# File spec/test_data/ruby_script.rb, line 5 5: def test_data 6: "ruby script" 7: end
Disabled; run with --debug to generate this.
[Validate]
Generated with the Darkfish Rdoc Generator 1.1.6.


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{{appState.appTitle$ | async}}
October 5, 2021 (v1.0.6)
- Update daemon(1.0.24) with latest checkpoint after BIP9 activation
September 7, 2021 (v1.0.5)
- Full revamp of the Rutanio-Core wallet UI
- Add Node Syncing dates feature, it is now possible to know from the Network status screen and from the tiptool of the top menu the remaining time for the node to synchronize
- Fix update details, from now on the list of changes and the download links of a new update are detailed
- Update daemon packages(1.0.23) to reduce the node time on start up for all platforms
- Update notification for 'No updates available'
- Add 'Reset database' option
- Add downloading and unpacking feature
- Add blink feature to download button
- Add API button in settings view
- Remove mac targets (dmg, zip)
- Add mac target pkg
- Add blink feature to download button
September 21, 2020 (v1.0.2)
- Initialization process fixed
- Installer package labels updated
September 11, 2020 (v1.0.1)
Preview release change history was purged.


Create your first alarm! To do so, you must set the following:
- Set a time (HH:MM) and time period (AM or PM)
- Select a charity to donate to when snooze is pressed (from the dropdown menu of 4 choices)
- Select an amount to donate each time you press snooze (in USD)
- Upload an image of an object far away from your bed that will need to be compared to when turning off the alarm.
- Wait for the alarm to ring … Maybe take a nap during this time.
- When the alarm rings, choose whether to turn it off by taking a photo of the object you initially uploaded (far away from your bed, requiring you to get up) OR snooze.
Beware: Snoozing sends money to the charity you chose!


Army conducts successful training launch of Shaheen-1 ballistic missile
by News DeskPakistan on Monday conducted a successful training launch of the Shaheen-1 ballistic missile, said a statement from the Inter-Services Public Relations (ISPR).
The training launch came a day after Pakistan’s arch-rival India conducted the first night trial of nuclear-capable intermediate-range Agni-II ballistic missile.
The Shaheen -1 is classified as a surface-to-surface ballistic missile, with a range of 650 kilometres. The missile can carry both conventional and nuclear warheads.
“The launch was conducted as part of a Training Exercise, which was aimed at testing the operational readiness of Army Strategic Forces Command.”
The military’s media wing added that troops of the Army’s strategic forces displayed a high standard of proficiency in handling potent missile system.
“The training launch was witnessed by Director General Strategic Plans Division, Commander Army Strategic Forces Command, Chairman NESCOM, senior officers from Strategic Plans Division, Army Strategic Forces Command, scientists and engineers,” said ISPR.
Earlier in May, the military conducted a successful training launch of the Shaheen-II surface-to-surface ballistic missile.
The test was in response to India testing the hypersonic Brahmos missile.


Tested.
More...
Tested.
- Bug:
- None documented yet
◆ __init__()
| def index.IndexItem.__init__ |
( |
|
self, |
|
|
|
term |
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) |
| |
The constructor.
- Parameters
-
- Returns
- None
- Exceptions
-
◆ add()
| def index.IndexItem.add |
( |
|
self, |
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docid, |
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|
|
pos |
|
) |
| |
This method adds a term position, for a Document to the postings list.
If this is the first time a document has been added to the posting list, the method creates a new posting (with docID) and then adds this the position the term was in the document. Otherwise, This method just adds the new position.
- Parameters
-
- Returns
- None
- Exceptions
-
◆ get_posting_list()
| def index.IndexItem.get_posting_list |
( |
|
self | ) |
|
This method return the posting list.
- Parameters
-
- Returns
- None
- Exceptions
-
◆ posting_list_to_string()
| def index.IndexItem.posting_list_to_string |
( |
|
self | ) |
|
This Method transforms the postings data into a dictionary format to be converted to Json.
- Parameters
-
- Returns
- posting: dict
- Exceptions
-
◆ return_sorted_posting()
| def index.IndexItem.return_sorted_posting |
( |
|
self | ) |
|
This method sort the posting list by document ID for more efficient merging.
And also sort each posting positions
- Parameters
-
- Returns
- sorted posting list and sorted dict posting list
- Exceptions
-
◆ set_posting_list()
| def index.IndexItem.set_posting_list |
( |
|
self, |
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|
|
docID, |
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posting |
|
) |
| |
This method sets the posting list.
- Parameters
-
- Returns
- None
- Exceptions
-
◆ sort()
| def index.IndexItem.sort |
( |
|
self | ) |
|
This method sort the posting list by document ID for more efficient merging.
And also sort each posting positions. sort by document ID for more efficient merging. For each document also sort the positions Firt sort all posting positions then sort doc id also creat new sorted dict. // not sure if need but why not
- Parameters
-
- Returns
- Noe
- Exceptions
-
◆ __posting
| index.IndexItem.__posting |
|
private |
◆ __sorted_dict
| index.IndexItem.__sorted_dict |
|
private |
◆ __sorted_postings
| index.IndexItem.__sorted_postings |
|
private |
◆ __term
The documentation for this class was generated from the following file:
- C:/Users/natcr/Desktop/College/CS 7800 Information Retrieva/Project/SimpleSearchEngine/src/index.py


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