import numpy as np

from statsmodels.tools.tools import Bunch

llf = np.array([-245.40783909604])

nobs = np.array([202])

k = np.array([5])

k_exog = np.array([1])

sigma = np.array([.8100467417583])

chi2 = np.array([2153.20304012])

df_model = np.array([3])

k_ar = np.array([1])

k_ma = np.array([2])

params = np.array([
    .92817025087557,
    -.89593490671979,
    1.3025011610587,
    .30250063082791,
    .8100467417583])

cov_params = np.array([
    .00638581549851,
    .0001858475428,
    2.8222806545671,
    .8538806860364,
    -1.1429127085819,
    .0001858475428,
    .00132037832566,
    -.14420925344502,
    -.04447007102804,
    .0576156187095,
    2.8222806545671,
    -.14420925344502,
    40397.568324803,
    12222.977216556,
    -16359.547340433,
    .8538806860364,
    -.04447007102804,
    12222.977216556,
    3698.2722243412,
    -4949.8609964351,
    -1.1429127085819,
    .0576156187095,
    -16359.547340433,
    -4949.8609964351,
    6625.0231409853]).reshape(5, 5)

xb = np.array([
    .92817026376724,
    .92817026376724,
    .69511789083481,
    .77192437648773,
    .66135895252228,
    .77525061368942,
    .64687132835388,
    .79659670591354,
    .65842008590698,
    .71215486526489,
    .69971066713333,
    .72092038393021,
    .68201982975006,
    .76510280370712,
    .64253836870193,
    .78239262104034,
    .64609551429749,
    .74087703227997,
    .71774411201477,
    .7119727730751,
    .73067259788513,
    .67785596847534,
    .70898467302322,
    .71334755420685,
    .72984194755554,
    .7017787694931,
    .75292426347733,
    .67507487535477,
    .78219056129456,
    .78040039539337,
    .71250075101852,
    .82028061151505,
    .63505899906158,
    .79452306032181,
    .72773635387421,
    .79555094242096,
    .76685506105423,
    .77427339553833,
    .82101213932037,
    .77917188405991,
    .78917801380157,
    .86641925573349,
    .78457218408585,
    .83697980642319,
    .83281791210175,
    .85224026441574,
    .75030690431595,
    .8551008105278,
    .78025943040848,
    .72790426015854,
    .84552866220474,
    .72061747312546,
    .78669738769531,
    .73868823051453,
    .78071022033691,
    .78002023696899,
    .83737623691559,
    .98988044261932,
    .72882527112961,
    1.2245427370071,
    .85331875085831,
    1.1637357473373,
    .86477434635162,
    1.3248475790024,
    .81245219707489,
    .98008638620377,
    .85591268539429,
    1.0162551403046,
    .8165408372879,
    .78947591781616,
    .94166398048401,
    .93266606330872,
    .85924750566483,
    1.1245046854019,
    .75576168298721,
    1.0030617713928,
    .91267073154449,
    1.0848042964935,
    1.0778224468231,
    1.1551086902618,
    .97817331552505,
    1.4012540578842,
    1.2360861301422,
    1.3335381746292,
    1.4352362155914,
    1.4941285848618,
    .9415163397789,
    1.437669634819,
    1.2404690980911,
    1.2285294532776,
    1.3219480514526,
    1.1560415029526,
    .83524394035339,
    .87116771936417,
    1.5561962127686,
    .47358739376068,
    .78093349933624,
    .90549737215042,
    1.0217791795731,
    .86397403478622,
    1.1526786088943,
    .87662625312805,
    .95803648233414,
    .89513635635376,
    .85281348228455,
    1.0852742195129,
    .76808404922485,
    .96872144937515,
    1.0732915401459,
    .02145584858954,
    1.3687089681625,
    .50049883127213,
    1.3895837068558,
    .6889950633049,
    1.2795144319534,
    .7050421833992,
    1.2218985557556,
    .74481928348541,
    1.3074514865875,
    .7919961810112,
    1.2807723283768,
    1.0120536088943,
    1.1938916444778,
    .68923074007034,
    1.6174983978271,
    .64740318059921,
    1.4949930906296,
    1.2678960561752,
    1.0586776733398,
    .55762887001038,
    1.2790743112564,
    .66515874862671,
    1.2538269758224,
    .70554333925247,
    1.2391568422318,
    .75241559743881,
    1.2129040956497,
    .69235223531723,
    1.0785228013992,
    .8043577671051,
    1.0037930011749,
    .78750842809677,
    1.1880930662155,
    .74399447441101,
    1.1791603565216,
    .85870295763016,
    1.0032330751419,
    .8019300699234,
    1.1696527004242,
    .92376220226288,
    .99186056852341,
    .94733852148056,
    1.0748032331467,
    .64247089624405,
    .95419937372208,
    .92043441534042,
    .8104555606842,
    .66252142190933,
    1.1178470849991,
    .69223344326019,
    1.0570795536041,
    .90239083766937,
    .95320242643356,
    1.0541093349457,
    1.0082466602325,
    1.1376332044601,
    1.1841852664948,
    .90440809726715,
    1.2733660936356,
    .66835701465607,
    1.1515763998032,
    .44600257277489,
    .93500959873199,
    1.0847823619843,
    .83353632688522,
    1.0442448854446,
    1.077241897583,
    .71010553836823,
    .89557945728302,
    1.0163468122482,
    1.094814658165,
    .89641278982162,
    1.2808450460434,
    1.0223702192307,
    .96094745397568,
    1.309353351593,
    .73499941825867,
    2.4902238845825,
    -.2579345703125,
    1.9272556304932,
    .53125941753387,
    .7708500623703,
    1.0312130451202,
    1.6360099315643,
    .6022145152092,
    1.6338716745377,
    1.3494771718979,
    1.1322995424271,
    2.1901025772095,
    -.72639065980911,
    -.37026473879814,
    1.2391144037247,
    1.1353877782822])

y = np.array([
    np.nan,
    29.908170700073,
    29.84511756897,
    30.121925354004,
    30.031360626221,
    30.315252304077,
    30.196870803833,
    30.5465965271,
    30.498420715332,
    30.52215385437,
    30.619710922241,
    30.70092010498,
    30.722021102905,
    30.975101470947,
    30.862537384033,
    31.162391662598,
    31.086095809937,
    31.220876693726,
    31.407745361328,
    31.461973190308,
    31.670673370361,
    31.627857208252,
    31.728984832764,
    31.833349227905,
    32.009841918945,
    32.08177947998,
    32.33292388916,
    32.325073242188,
    32.662189483643,
    33.060398101807,
    33.162502288818,
    33.670280456543,
    33.535060882568,
    33.894519805908,
    34.127738952637,
    34.495552062988,
    34.866851806641,
    35.17427444458,
    35.721012115479,
    36.079170227051,
    36.489177703857,
    37.16641998291,
    37.584571838379,
    38.136978149414,
    38.732818603516,
    39.352241516113,
    39.65030670166,
    40.255104064941,
    40.68025970459,
    40.827903747559,
    41.445526123047,
    41.620620727539,
    41.986698150635,
    42.238689422607,
    42.580707550049,
    42.98002243042,
    43.537376403809,
    44.689880371094,
    44.928825378418,
    46.824542999268,
    47.653316497803,
    49.263732910156,
    50.164772033691,
    52.324848175049,
    53.112449645996,
    53.980087280273,
    54.855911254883,
    55.916255950928,
    56.616539001465,
    56.889472961426,
    57.941665649414,
    58.832668304443,
    59.55924987793,
    61.124504089355,
    61.555759429932,
    62.603061676025,
    63.612670898438,
    64.984802246094,
    66.577819824219,
    68.255104064941,
    69.478172302246,
    72.001251220703,
    74.236083984375,