import numpy as np

from statsmodels.tools.tools import Bunch


mpg_bs_poisson = Bunch()

mpg_bs_poisson.smooth0 = Bunch()
mpg_bs_poisson.smooth0.term = 'weight'
mpg_bs_poisson.smooth0.bs_dim = 12
mpg_bs_poisson.smooth0.dim = 1
mpg_bs_poisson.smooth0.p_order = np.array([
    3, 2
    ])
mpg_bs_poisson.smooth0.by = 'NA'
mpg_bs_poisson.smooth0.label = 's(weight)'
mpg_bs_poisson.smooth0.sp = -1
mpg_bs_poisson.smooth0.m = np.array([
    3, 2
    ])
mpg_bs_poisson.smooth0.knots = np.array([
    1488, 1488, 1488, 1488, 1953.22222222, 2118.77777778, 2275,
    2383.88888889, 2515.55555556, 2757.33333333, 3016.44444444,
    3208.11111111, 4066, 4066, 4066, 4066
    ])
mpg_bs_poisson.smooth0.rank = 10
mpg_bs_poisson.smooth0.null_space_dim = 1
mpg_bs_poisson.smooth0.df = 11
mpg_bs_poisson.smooth0.S_scale = 2.44395544177397e-06
mpg_bs_poisson.smooth0.vn = 'weight'
mpg_bs_poisson.smooth0.first_para = 5
mpg_bs_poisson.smooth0.last_para = 15
mpg_bs_poisson.smooth0.S = np.array([
    0.130569121544375, -0.0191732921244136, 0.0202548028417763,
    0.0393112950002946, 0.032061392663319, 0.0241651485426007,
    0.0238771778381105, 0.0389406835250852, 0.0171569521441248,
    0.00680570834700402, 0.00541920498010491, -0.0191732921244136,
    0.0631473273216884, -0.0592997810399249, 0.0178641542128365,
    0.00461438941034586, 0.00793912465273829, 0.00408821971418319,
    -0.000681869049168392, 0.00213834646721613, 0.000935846814259467,
    0.000163463753965317, 0.0202548028417763, -0.0592997810399249,
    0.201022514824508, -0.186241322892132, 0.00284878067469136,
    0.0287314367063779, 0.00263260805442764, -0.00708846456492193,
    0.00065385484055723, 0.000395067932117418, -0.000586348849229599,
    0.0393112950002947, 0.0178641542128365, -0.186241322892132,
    0.479322071007576, -0.286380917395105, 0.0563704638942206,
    0.0348887744557148, 0.0255203052273876, 0.0138979985789615,
    0.00560832050247454, 0.00383270204450356, 0.032061392663319,
    0.00461438941034587, 0.00284878067469137, -0.286380917395105,
    0.414581586658592, -0.181289913269406, -0.00412646444222532,
    -0.00354719180127285, -0.00206283566879658, -0.000685858743449883,
    -0.00142523589453221, 0.0241651485426007, 0.00793912465273829,
    0.0287314367063779, 0.0563704638942206, -0.181289913269406,
    0.213321319885371, -0.0483506678191679, 0.0110304252072989,
    0.0122299348640366, 0.00357726593043956, 0.00234383478372281,
    0.0238771778381105, 0.00408821971418319, 0.00263260805442764,
    0.0348887744557148, -0.00412646444222533, -0.0483506678191679,
    0.0999220996092033, -0.0356092452156359, 0.00921547832469341,
    0.00389860712399989, 0.00147745030481206, 0.0389406835250852,
    -0.000681869049168392, -0.00708846456492192, 0.0255203052273876,
    -0.00354719180127286, 0.0110304252072989, -0.0356092452156359,
    0.0574427000604467, -0.0102653399490586, -0.000311188772793241,
    0.00285258581655637, 0.0171569521441248, 0.00213834646721613,
    0.000653854840557233, 0.0138979985789615, -0.00206283566879658,
    0.0122299348640366, 0.00921547832469341, -0.0102653399490586,
    0.0189789273643945, -0.0062453384832703, 0.00255839876648785,
    0.00680570834700402, 0.000935846814259467, 0.000395067932117419,
    0.00560832050247454, -0.000685858743449884, 0.00357726593043956,
    0.00389860712399989, -0.000311188772793241, -0.0062453384832703,
    0.0211496391608495, -0.0111654555301857, 0.00541920498010491,
    0.000163463753965317, -0.000586348849229599, 0.00383270204450356,
    -0.00142523589453221, 0.00234383478372281, 0.00147745030481206,
    0.00285258581655637, 0.00255839876648785, -0.0111654555301857,
    0.00794139033444708
    ]).reshape(11, 11, order='F')

mpg_bs_poisson.coefficients = np.array([
    3.38155196812657, -0.2398057983025, 0.0385574655971876,
    0.0308789097162079, 0.322087207070371, 0.114222640046661,
    -0.0703319473834318, -0.0932993942273026, -0.164529819124519,
    -0.150860338924587, -0.19827414261489, -0.318132823476157,
    -0.277920321049033, -0.291752287584618, -0.335850782440607,
    0.147266917321495, 0.0655746640077953, 0.00329634588440575,
    -0.0178203244735351, -0.0949069908870388, -0.162736107333124,
    -0.267760412623755, -0.31426029441775, -0.36537967845964
    ])
mpg_bs_poisson.residuals = np.array([
    -0.0597164611104715, -0.0597164611104715, 0.0070681780740447,
    -0.0244130279937029, -0.109459035981563, -0.167042459441988,
    -0.105640645333752, -0.0887544418878843, -0.0954712805695528,
    -0.0784623437350325, -0.0430169241934606, -0.0430169241934606,
    0.0030916078609633, 0.0137773951290736, 0.0148539285398903,
    -0.0370396919392229, -0.0112736908607727, -0.052100214301857,
    0.05696516521011, 0.132586599766586, 0.152452919091744,
    0.0958117450422904, -0.0818874568564589, -0.0996285128088896,
    -0.039947957328768, -0.0297876572186078, -0.0297876572186078,
    -0.0757627215899457, -0.0131089324697808, -0.0233738731200743,
    0.286760172557162, -0.0814957361302606, 0.0714671532989226,
    -0.0558415218265038, -0.0484787948859533, -0.0236434176492324,
    -0.0172259149323173, 0.00318143181414277, 0.0231117802042631,
    0.0285924230117791, 0.0524599141234474, 0.0116354361716793,
    -0.00558296033674166, -0.0940825558878515, 0.132586599766586,
    0.152452919091744, 0.0461585732431811, 0.036440559843717,
    0.036440559843717, 0.00758219423801565, -0.105282911203192,
    -0.0708600665943635, -0.0685585970304921, -0.0501105407364437,
    -0.0478013558335348, -0.295992218769999, -0.295992218769999,
    -0.294876506179699, -0.243930144705301, 0.010594364536701,
    0.0184495378782166, 0.010594364536701, 0.0184495378782166,
    0.0421491667369525, 0.0230515193544041, -0.102317831424696,
    -0.00921877268202032, -0.04273337969419, -0.00119636037327275,
    -0.0461713804461907, 0.00242207736643074, -0.00206774027200307,
    -0.0119510982296829, -0.0463162166023352, -0.0776191103317818,
    0.0686101070886802, 0.118868895618542, -0.0505723217649421,
    -0.0228687782317891, -0.0931020215865397, -0.0139373055232768,
    -0.0329425423946335, -0.019547742575587, -0.00462341430485536,
    -0.0037863985625175, -0.0209367502247506, -0.00850079663664394,
    -0.00363892191661508, -0.00363892191661508, -0.0725184022338961,
    0.0701390830766382, -0.0591199977863917, -0.0498592974299408,
    -0.0100344019333893, -0.0438341236186641, -0.00819025184245747,
    -0.0345607099570335, -0.00404629308005688, -0.017423468562916,
    0.0751572654869439, 0.0669394971058765, -0.0679255314192151,
    -0.0349740550587878, 0.0355822453431487, 0.0642764024494471,
    0.0402581086152893, 0.0766500282298974, -0.108739714671304,
    0.0579475740333115, -0.0762240417848723, -0.0158254364629684,
    -0.106391902749726, 0.0681088212932508, -0.073453881324304,
    -0.00607566275315818, -0.100457295597509, 0.0681088212932508,
    -0.0228550021478378, 0.118868895618542, -0.0996285128088896,
    -0.039947957328768, -0.0297876572186078, 0.0607856968972396,
    -0.0131089324697808, -0.0146135261048062, -0.0264261656715257,
    -0.0145337592605999, -0.0145337592605999, -0.0064905487190714,
    0.226809817977968, -0.0459953733057028, -0.0386603873101858,
    -0.0363408944476897, -0.0267731783454677, 0.00999638170999839,
    0.0169931451495056, 0.00192444906825173, -0.120308776123272,
    -0.0400164322133238, 0.130247697154032, 0.00746981127430812,
    0.0306709674011021, -0.0372819368771609, 0.0976557161110208,
    0.0465873287478877, 0.0269883944212412, -0.0674146853454123,
    0.0873341779571093, 0.0693951026504345, -0.0280641297469413,
    -0.0392924504624044, 0.0735437039091389, -0.0247046596041458,
    0.171463552666685, -0.013091147087648, -0.000813946803385424,
    -0.0956269920449824, 0.0107698324203134, 0.25732769645148,
    -0.0621561621420588, -0.0549179845713752, -0.00160856625504557,
    0.0126062678583092, 0.0705449231002744, 0.0842095493097967,
    0.0883081440038147, 0.0872170109597095, 0.0912812221820642,
    0.123175492931149, 0.131142517763956, 0.184711504210098,
    0.136459914352958, -0.0929831907336212, 0.0885449049874016,
    0.0885449049874016, 0.102638885670704, 0.104987186006888,
    0.0567660298014965, 0.121868643941937, 0.0694291967778775,
    -0.0353205301526058, -0.0107460163888975, -0.0342456641975604,
    -0.00957686458378415, 0.0143852426645283, 0.0450346063721021,
    0.0367753899157743, -0.0896986969406739, -0.101104390140708,
    -0.136305098940538, 0.00460226286555798, 0.0351388253204785,
    0.116934978569832, 0.13995662419881, 0.170013018072364,
    0.191118649321067, -0.0478214884195327, -0.0295329898984451,
    0.124455798890416, 0.0603367500448151, -0.0610962381564639,
    0.0212222309861203, -0.0538512733755478
    ])
mpg_bs_poisson.fitted_values = np.array([
    22.3336888624052, 22.3336888624052, 18.8666471780851, 24.6005745142783,
    20.2124334840001, 22.8102863289666, 21.2442570213741, 20.8505817458946,
    18.7943175653995, 17.3622856225417, 24.0338628565774, 24.0338628565774,
    20.9352763351109, 20.7146066788422, 19.7072696252699, 16.6154304243557,
    16.1824357783393, 15.8244576339389, 44.4669337713292, 33.5515182749217,
    32.9731474236258, 33.764923735666, 33.764923735666, 26.6556641802072,
    32.2899161942785, 31.9517683223134, 31.9517683223134, 25.9673576911837,
    24.3187934206985, 19.4547324478203, 38.080134157885, 33.7505237802536,
    35.4653895670086, 31.7743267613674, 31.5284618343364, 30.7264789753035,
    30.5258354446067, 26.9143737550779, 26.3900783105141, 26.2494642153229,
    25.6541837248854, 23.723961361835, 25.1403576194408, 26.4924802541156,
    33.5515182749217, 32.9731474236258, 22.9410728104038, 14.4726099895799,
    14.4726099895799, 12.9021732165794, 33.5301520174866, 33.3641886280506,
    33.2817500931026, 32.6353763563543, 32.5562320319588, 24.1474603736604,
    24.1474603736604, 24.1092519948462, 21.1620657641, 25.7274341836643,
    25.5290017158504, 25.7274341836643, 25.5290017158504, 34.5439992172317,
    25.4141648862486, 21.1656203778165, 31.2884410253879, 22.9821029307089,
    22.0263514540474, 23.0649401255032, 21.9468430481884, 16.0331523948941,
    16.1935304733726, 14.6799182745066, 15.1781115120846, 17.7801050860014,
    33.0691112648595, 32.6512494955146, 31.725523972003, 26.4638366952653,
    23.3250888902206, 25.8516180226821, 19.3788120289629, 19.0882529015196,
    19.0722150074884, 25.5346117891147, 25.2143419936145, 23.0840008767134,
    23.0840008767134, 33.4238437448952, 42.0506088522863, 32.9478785042368,
    32.6267466662015, 31.3142194643355, 32.4211528205977, 31.2559944662652,
    32.1097352466569, 31.1259446946281, 31.5497052984366, 25.1126052594469,
    25.3060272613759, 18.2388860257967, 17.6161066851271, 18.3471666161138,
    17.8525051915754, 16.3420980420225, 17.6473315393281, 21.3181270530784,
    26.4663398142244, 20.5677576159384, 25.401997700644, 21.2621170941322,
    26.2145573950957, 20.5062647363485, 25.1528200519264, 21.1218432510333,
    26.2145573950957, 18.4210122751131, 33.0691112648595, 26.6556641802072,
    32.2899161942785, 31.9517683223134, 29.2236217839983, 24.3187934206985,
    19.2817747181913, 19.5157258032775, 17.2507177792766, 17.2507177792766,
    17.1110601696662, 13.8570785388883, 22.01247186061, 21.8445175074418,
    21.7919385382283, 21.5777037097056, 18.8119485812727, 18.6825251385611,
    30.9404566669959, 29.5558251512617, 27.0837969236757, 28.3123779686312,
    27.7923960466705, 25.2262854221658, 24.92941694908, 21.8647793180832,
    26.7536202960708, 24.343020949218, 24.662622967121, 21.1526506443608,
    32.7287827606976, 31.8951084621752, 32.2678842431506, 28.8763278915599,
    27.6839218662126, 23.048092224925, 30.3979439554833, 30.0244382955741,
    37.5951069978098, 37.5951069978098, 30.2228290263917, 29.8557167725841,
    29.6270583323936, 29.0467235793694, 28.6389694795548, 24.2866968391243,
    23.9806041337226, 22.052577785282, 22.0747097939672, 21.9924979117765,
    21.3679875950349, 21.2174855273261, 20.2580965194576, 25.5178380106008,
    33.0754619909028, 24.8037539620954, 24.8037539620954, 24.4867112441592,
    18.0997574028658, 17.9793818727964, 17.8273990524644, 17.7664870729599,
    38.3547086431239, 27.2932941866366, 38.3120205919209, 27.2610756297141,
    26.6171064644809, 35.4055260700386, 25.0777557539364, 26.3648968966003,
    26.6994295408305, 21.998508937234, 32.8488210905178, 24.1513499334353,
    20.5920670775752, 20.1762062799231, 20.5125922782815, 20.1491262131442,
    17.8537950533904, 17.5173394077775, 20.4543389101606, 17.9188356898853,
    19.171293940347, 25.4596886075362, 20.0814094711999
    ])
mpg_bs_poisson.linear_predictors = np.array([
    3.10609624980832, 3.10609624980832, 2.93739566357681, 3.20276979690456,
    3.00629793406294, 3.12721158899991, 3.05608660102651, 3.03738184933733,
    2.9335545669874, 2.85430036085041, 3.17946378824737, 3.17946378824737,
    3.04143559905492, 3.03083908808588, 2.98098758418526, 2.81033180724024,
    2.78392644284256, 2.76155669470604, 3.79474585164685, 3.51308211648978,
    3.4956935157856, 3.51942250434414, 3.51942250434414, 3.28300166762353,
    3.4747549893589, 3.46422752584326, 3.46422752584326, 3.25684027583847,
    3.19124944323147, 2.96809035398114, 3.63969273297066, 3.51899593661304,
    3.56855727914211, 3.45865862916789, 3.45089068817213, 3.42512479018631,
    3.41857338881492, 3.2926604842363, 3.27298811794221, 3.26764557798449,
    3.24470666649875, 3.1664855653221, 3.2244744281779, 3.27686092872792,
    3.51308211648978, 3.4956935157856, 3.13292887653641, 2.67225789684402,
    2.67225789684402, 2.55739576358026, 3.51244509424318, 3.50748312800355,
    3.50500920150253, 3.48539686431283, 3.48296881060363, 3.18417921405787,
    3.18417921405787, 3.18259566702687, 3.05221022812765, 3.24755790051531,
    3.23981512809367, 3.24755790051531, 3.23981512809367, 3.54223385111242,
    3.23530669126982, 3.05237818503949, 3.44324873302594, 3.13471577957874,
    3.09223952994195, 3.13831372110367, 3.08862330449352, 2.77465860323819,
    2.78461180897998, 2.68648045603917, 2.71985435790984, 2.87808014041708,
    3.49859965227091, 3.48588312437807, 3.45712152952405, 3.27577914799641,
    3.14952955766808, 3.25237319174925, 2.96418030576864, 2.94907311450918,
    2.9482325642825, 3.24003485689474, 3.22741295935692, 3.13913977482799,
    3.13913977482799, 3.50926952986597, 3.73887386555994, 3.4949268735718,
    3.48513240187112, 3.44407229037009, 3.47881107460801, 3.44221118070723,
    3.46915926286833, 3.43804170595891, 3.45156424816504, 3.22336992164832,
    3.23104259903575, 2.90355590963404, 2.86881363611135, 2.90947515473725,
    2.88214384524492, 2.79374448033398, 2.87058458437584, 3.05955774614591,
    3.27587372992023, 3.02372468537151, 3.23482782056342, 3.0569269490534,
    3.26631488223122, 3.02073043635419, 3.22497001956098, 3.05030773017343,
    3.26631488223122, 2.91349198453504, 3.49859965227091, 3.28300166762353,
    3.4747549893589, 3.46422752584326, 3.37497734744367, 3.19124944323147,
    2.9591603346448, 2.97122059201258, 2.84785375300452, 2.84785375300452,
    2.83972504797555, 2.62879618791377, 3.09160919548466, 3.08394997506595,
    3.0815401095808, 3.07166054590621, 2.93449223078504, 2.92758860238871,
    3.43206460479669, 3.38628085306311, 3.29893564957711, 3.34329909307524,
    3.32476245978116, 3.22788652320362, 3.21604850974011, 3.08487709188384,
    3.2866698023555, 3.1922451944518, 3.20528885733209, 3.05176522361415,
    3.48825489749758, 3.46245265828934, 3.47407243971087, 3.36302215537105,
    3.32085180663105, 3.13758299920276, 3.41437497308165, 3.4020116599001,
    3.62687390889084, 3.62687390889084, 3.40859756683735, 3.39637633817112,
    3.38868807661617, 3.36890569137327, 3.35476835958596, 3.18992874525813,
    3.17724534251483, 3.09342950142183, 3.09443260003746, 3.09070139119307,
    3.06189389526813, 3.05482563075123, 3.00855454176395, 3.23937773743491,
    3.49879167788239, 3.21099501115507, 3.21099501115507, 3.19813057220198,
    2.89589853502537, 2.88922564985387, 2.88073654644261, 2.8773139339888,
    3.64687730106182, 3.30664103782876, 3.64576370051983, 3.30545988365993,
    3.28155410925581, 3.56686791163023, 3.22198122826548, 3.27203346235845,
    3.28464219966599, 3.09097467548117, 3.49191585663117, 3.18434027640117,
    3.02490590830647, 3.00450400319504, 3.0210389550426, 3.00316092334049,
    2.88221609366084, 2.86319121368963, 3.01819503162959, 2.88585243277332,
    2.95341405297199, 3.23709636239996, 2.99979448514897
    ])
mpg_bs_poisson.deviance = 37.5688885982924
mpg_bs_poisson.null_deviance = 337.261844954099
mpg_bs_poisson.iter = 2
mpg_bs_poisson.weights = np.array([
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mpg_bs_poisson.working_weights = np.array([
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