"""
This file contains the residuals for testing GLM.

All residuals were obtained with Stata.

The residuals are column ordered as

Pearson, Deviance, Working, Anscombe, and Response Residuals
"""


import numpy as np

# TODO: wrap super-long lines.  maybe put these in csv files?
lbw = [-.67369007, -.86512534, -.06703079, -.93506245, -.31217507, -.38301082, -.52323205, -.01427243, -.55879206, -.12793027, -.68788286, -.88025592, -.07003063, -.95205459, -.32119762, -.96932399, -1.1510657, -.12098923, -1.2626094, -.48442686, -1.017216, -1.1919416, -.12709645, -1.3106868, -.50853393, -.56992387, -.75002865, -.04537362, -.80685236, -.24517662, -.38236113, -.52240243, -.01419429, -.5578939, -.12755193, -.70541551, -.89874491, -.07371959, -.97286469, -.33226988, -.53129095, -.70516948, -.03779124, -.75734471, -.22013309, -.59687896, -.78068461, -.05087588, -.84082824, -.26268069, -.72944938, -.92372831, -.07872676, -1.0010676, -.34729955, -.48089188, -.64503581, -.02865125, -.6913447, -.18782188, -1.7509231, -1.6748694, -.13984667, -1.9107428, -.75404181, -1.0993874, -1.2588746, -.13558784, -1.3901949, -.54723527, -.73406378, -.9284774, -.0796795, -1.0064397, -.35016393, -.73406378, -.9284774, -.0796795, -1.0064397, -.35016393, -.91970083, -1.1071944, -.11376204, -1.2113902, -.45824406, -.58253395, -.76443611, -.04792993, -.8228052, -.25336683, -.87010277, -1.0617464, -.10565948, -1.1587271, -.43087357, -.55091811, -.72809506, -.04159148, -.78261562, -.23284101, -.50228984, -.67078749, -.03241138, -.71955949, -.20146616, -.56681231, -.74645574, -.04474827, -.80290024, -.24315597, -.16739043, -.23509228, -.00072263, -.24969795, -.02725586, -.53429779, -.70869969, -.03836573, -.76123202, -.22207692, -.81310524, -1.0074762, -.09536044, -1.0963421, -.39800383, -.24319644, -.339003, -.00294417, -.36060255, -.05584178, -.62985338, -.81746346, -.05776093, -.88175202, -.28403447, -.27289888, -.37902784, -.00447115, -.403468, -.06931188, -.73980785, -.9343678, -.08086098, -1.0131078, -.35371946, -.79896487, -.99366645, -.09266053, -1.0805507, -.3896279, -.79896487, -.99366645, -.09266053, -1.0805507, -.3896279, -.95715693, -1.140454, -.11930111, -1.2501848, -.47812002, -1.2258645, -1.3545388, -.14405247, -1.5056478, -.60043853, -.27739012, -.38504179, -.00474005, -.40991694, -.07144772, -.65459114, -.84453257, -.06298676, -.91198968, -.29995988, -.46709275, -.62825848, -.02633193, -.67300059, -.17910031, -.54303849, -.71892471, -.04005189, -.77249964, -.22773411, -.54176628, -.71743989, -.03980502, -.77086265, -.22691015, -.25756493, -.35841857, -.00362961, -.38138453, -.06221253, -.55956791, -.73810992, -.04330137, -.79367479, -.2384528, -.69600671, -.88885063, -.07174285, -.96172188, -.32633864, -.23256318, -.32457262, -.00249768, -.34516994, -.05131047, -.64757466, -.83690034, -.06150185, -.90345369, -.2954536, -.28195528, -.39114407, -.00502406, -.41646289, -.07364416, -1.1570243, -1.3035317, -.14010172, -1.443813, -.57241299, -1.1570243, -1.3035317, -.14010172, -1.443813, -.57241299, -.30030789, -.41556527, -.00627721, -.44268348, -.08272435, -.55114605, -.72835967, -.04163627, -.78290767, -.23298882, -.3806923, -.52027022, -.01399469, -.5555858, -.12658158, -1.1987876, -1.33477, -.1426768, -1.4816055, -.58967487, -.94149929, 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-.01580695, -.57585866, -.13519643, -.95811737, -1.141295, -.11943637, -1.2511687, -.47862055, -.79777479, -.99249783, -.09243093, -1.0792158, -.38891913, -.4007824, -.54582043, -.01650278, -.58326946, -.1383964, -.59547213, -.77909775, -.05058538, -.83906658, -.26176764, -.67961214, -.87145655, -.06828352, -.9421685, -.31594589, -.35903387, -.49243968, -.01154966, -.52549403, -.11418612, -.25982794, -.36146745, -.00374651, -.38464992, -.06324112, -.63086237, -.8185763, -.0579734, -.88299313, -.28468594, -.52587777, -.6987977, -.03676448, -.75033205, -.21663702, -.19948442, -.27936589, -.00140862, -.29689136, -.03827107, -.61183026, -.7974596, -.05398148, -.85947135, -.27237604, -.50385167, -.67265442, -.03269316, -.72160779, -.20246694, -.48499858, -.65000311, -.02935791, -.69678155, -.19042999, -.42040434, -.57052211, -.01917023, -.61008878, -.15019447, -.48053382, -.64460216, -.02858999, -.69087017, -.18759474, -.37464721, -.51253189, -.01328506, -.54721232, -.12308435, -.49531764, -.66243224, -.03116534, -.71039719, -.19700616, -.36160926, -.49576422, -.01182621, -.52908537, -.11564002, -.75971278, -.95459728, -.08491171, -1.0360505, -.36595033, -.29016492, -.40209055, -.00556233, -.42821114, -.07765727, -.40546611, -.55173962, -.01712019, -.58969106, -.14119063, -.39648646, -.54037876, -.01594727, -.57736865, -.13584627, -.35179057, -.48306766, -.01079245, -.51537461, -.11012759, -.33522775, -.46151868, -.00917494, -.49213296, -.10102472, -.33337344, -.45909602, -.00900368, -.48952221, -.10002166, -.28349954, -.39320584, -.00512259, -.41867509, -.07439288, -.62237174, -.80918847, -.05618813, -.87252863, -.27919958, -.37781929, -.51659535, -.01365481, -.55160868, -.12491598, -.26957183, -.37456618, -.00427859, -.39868504, -.06774594, .61566918, .80174036, .05478366, .86423481, .27486236, 2.1552118, 1.8605156, .11994504, 2.1616254, .82285014, .6958925, .88873013, .07171881, .96158626, .32626648, .48936001, .65526554, .03011636, .70254431, .19320564, .94341916, 1.1283597, .11732917, 1.2360523, .47091059, 2.317558, 1.9244575, .11155378, 2.2513666, .84304062, 1.0055755, 1.1821359, .12569111, 1.2991214, .50277997, 1.1758629, 1.3177365, .14133315, 1.4609684, .58029986, .77665994, .97159873, .08829985, 1.0553839, .37624776, .92862761, 1.1152029, .11512854, 1.2207114, .46304378, 1.7104194, 1.6537851, .14148619, 1.8830756, .74525762, .51347062, .68411403, .03444926, .73418924, .20864293, 1.7302647, 1.6641798, .14069739, 1.8966961, .7496129, 1.7159282, 1.656683, .14127016, 1.886869, .74647663, 1.4097427, 1.4794559, .14814617, 1.659967, .66525789, 2.0442483, 1.8136166, .12572138, 2.0969416, .80691071, 1.7479484, 1.6733383, .13997094, 1.9087284, .75341056, 1.7094805, 1.6532902, .14152278, 1.8824281, .74504908, 1.4965596, 1.5332827, .14752494, 1.7278315, .69132856, 1.1936562, 1.330981, .14239054, 1.4770087, .58759741, .82652693, 1.0204559, .09787281, 1.1112146, .40587474, 2.2245013, 1.8884508, .11633994, 2.2006058, .83188774, 1.0349547, 1.206727, .12914052, 1.3281647, .51717209, 1.3170894, 1.4184715, .14713645, 1.5840959, .63433244, 3.1267629, 2.1805419, .07637108, 2.631322, .90720675, .57215628, .7525877, .04582366, .809684, .24662647, .86627248, 1.0581685, .10499903, 1.1545978, .42871115, .94218582, 1.1272681, .11714873, 1.2347781, .47025877, 1.1156811, 1.2716852, .13698079, 1.405528, .55451496, .53496988, .70948787, .03849454, .76210013, .22251157, 1.4497097, 1.5046175, .14802749, 1.6915825, .6775918, 1.2233611, 1.3527267, .14393463, 1.5034398, .59945723, 1.545073, 1.5620618, .14664053, 1.7644793, .70477532, 2.020635, 1.803272, .12694042, 2.0827983, .80326447, .59611095, .7798185, .05071725, .83986668, .26218226, .85655928, 1.0490513, .1033029, 1.144086, .42319688, 1.1157473, 1.2717369, .13698625, 1.40559, .55454427, 1.5187563, 1.5465618, .1471632, 1.7447092, .69757645, 1.2580261, 1.3775399, .14540261, 1.5337471, .61279777, 2.2387897, 1.8940894, .11559989, 2.2085158, .83367096, 1.4987735, 1.5346157, .14749226, 1.7295233, .69195908, .87949714, 1.0704799, .10725881, 1.1688167, .43614806, .81628943, 1.0105668, .09596102, 1.0998807, .39987821, 1.0340841, 1.2060057, .12904294, 1.327311, .51675179, 1.7490122, 1.6738861, .13992657, 1.9094491, .75363655, 1.6803635, 1.6378022, .14262258, 1.8622063, .73846784, 1.8051113, 1.7022925, .13748913, 1.9469661, .7651715, 1.5637979, 1.5729326, .14621078, 1.7783904, .70976331, 1.1993095, 1.3351545, .14270545, 1.4820722, .58988546, 1.3197815, 1.4202979, .1471939, 1.5863531, .63527917, .71898726, .91290406, .07655565, .98883657, .34077931, 1.5103554, 1.5415584, .14730892, 1.7383434, .69523097, 3.0022063, 2.1465826, .08091665, 2.5788383, .90013225, .64440768, .83344364, .06083212, .89959036, .29341668, 1.5019795, 1.5365427, .14744358, 1.7319699, .69286925, 1.3305489, 1.4275696, .1474058, 1.5953487, .63903614, .90521582, 1.094089, .11148405, 1.1961638, .45037299, .6236701, .81062745, .05646071, .87413186, .28003914, .71234937, .90599551, .07517106, .9810397, .3366244]

lbw_resids = np.array(lbw).astype(float).reshape(-1, 5)

cpunish = [.29883413, .29637762, 62.478695, .29638095, 1.7736344, .280627, .27622019, 6.5853375, .27623151, .80342558, 4.0930531, 2.9777878, 6.1503069, 3.0157174, 4.6881034, .16338859, .16114971, 1.1563983, .16115474, .31370176, .63595872, .59618385, 1.9109264, .59656954, .91769973, .9059739, .8066189, .99577089, .80822353, .9349684, .0532905, .0529548, .14244545, .05295515, .07395759, -.26830664, -.2766384, -1.0082872, -.27668319, -.41714051, -.62341484, -.68349824, -1.5652763, -.68459104, -.84732188, -1.1015655, -1.2743561, -5.3400286, -1.279951, -1.8643241, -1.2006618, -1.4021282, -6.6206839, -1.40923, -2.1211989, -1.2797534, -1.505173, -7.8054171, -1.5136295, -2.3382067, -.960585, -1.0954134, -3.8587164, -1.0992211, -1.5269969, .10846917, .10649195, .0921891, .10649783, .1027458, .02088367, .02081086, .02023963, .0208109, .02066675, .63647875, .56713011, .24880139, .56824372, .4653791, -.69597083, -.77000601, -1.9377178, -.77151335, -.97909358]

cpunish_resids = np.array(cpunish).astype(float).reshape(-1, 5)

scotvote = [.04317472, .04256856, -8338.93, .04256786, 2.4956853, -.01827077, -.01838325, 2762.4019, -.01838319, -.97334528, .05609817, .05508221, -7252.03, .05508069, 2.8365188, -.02280193, -.02297758, 4525.3102, -.02297747, -1.3300374, -.02505649, -.02526888, 8767.023, -.02526873, -1.7656214, -.1421743, -.14953291, 26174.801, -.14950069, -8.0880132, -.01973673, -.01986809, 5888.0406, -.01986801, -1.318784, .06763015, .06616299, -19473.553, .06616036, 4.4658962, .0202078, .02007327, -3928.3996, .02007319, 1.1706255, -.00841611, -.00843983, 2127.7741, -.00843983, -.53216875, -.04429363, -.04496504, 6971.3512, -.04496419, -2.3914787, .01158536, .01154092, -2667.3324, .01154091, .71006619, .05538677, .05439602, -15077.849, .05439455, 3.5896364, .09018494, .08760809, -23064.91, .087602, 5.7245313, .06595122, .06455471, -14747.68, .06455226, 4.0030388, .00220373, .00220212, -923.58004, .00220212, .16491647, .09775671, .09474141, -17697.14, .09473373, 5.5300885, -.0669005, -.06845346, 24989.253, -.06845044, -4.8180428, .05194846, .05107522, -13846.987, .05107401, 3.3432347, .01298505, .01292927, -1828.3796, .01292925, .67554021, .02257874, .02241101, -5988.3279, .02241091, 1.4506691, .01474752, .01467564, -5311.9833, .01467562, 1.0492967, .03640993, .03597719, -3483.054, .03597677, 1.665201, -.06613827, -.06765534, 10963.702, -.06765242, -3.633186, -.05046726, -.05134215, 15165.308, -.05134088, -3.3803129, -.02546479, -.02568421, 3585.6787, -.02568405, -1.3248006, -.08159133, -.08392239, 14470.556, -.08391679, -4.5841388, -.0330796, -.03345156, 6495.2667, -.03345121, -1.9226747, .00327289, .00326933, -1001.1863, .00326933, .22052594, -.02631155, -.02654593, 5824.1466, -.02654575, -1.5916286, .01183737, .01179098, -4763.0477, .01179097, .87390689, -.03325649, -.03363248, 11219.87, -.03363212, -2.3151557]

scotvote_resids = np.array(scotvote).astype(float).reshape(-1, 5)

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star98_resids = np.array(star98).astype(float).reshape(-1, 5)

