import numpy as np

from statsmodels.tools.tools import Bunch

llf = np.array([-240.29558272688])

nobs = np.array([202])

k = np.array([5])

k_exog = np.array([1])

sigma = np.array([.79494581155191])

chi2 = np.array([1213.6019521322])

df_model = np.array([3])

k_ar = np.array([2])

k_ma = np.array([1])

params = np.array([
    .72428568600554,
    1.1464248419014,
    -.17024528879204,
    -.87113675466923,
    .63193884330392])

cov_params = np.array([
    .31218565961764,
    -.01618380799341,
    .00226345462929,
    .01386291798401,
    -.0036338799176,
    -.01618380799341,
    .00705713030623,
    -.00395404914463,
    -.00685704952799,
    -.00018629958479,
    .00226345462929,
    -.00395404914463,
    .00255884492061,
    .00363586332269,
    .00039879711931,
    .01386291798401,
    -.00685704952799,
    .00363586332269,
    .00751765532203,
    .00008982556101,
    -.0036338799176,
    -.00018629958479,
    .00039879711931,
    .00008982556101,
    .00077550533053]).reshape(5, 5)

xb = np.array([
    .72428566217422,
    .72428566217422,
    .56208884716034,
    .53160965442657,
    .45030161738396,
    .45229381322861,
    .38432359695435,
    .40517011284828,
    .36063131690025,
    .30754271149635,
    .32044330239296,
    .29408219456673,
    .27966624498367,
    .29743707180023,
    .25011941790581,
    .27747189998627,
    .24822402000427,
    .23426930606365,
    .27233305573463,
    .23524768650532,
    .26427435874939,
    .21787133812904,
    .22461311519146,
    .22853142023087,
    .24335558712482,
    .22953669726849,
    .25524401664734,
    .22482520341873,
    .26450532674789,
    .31863233447075,
    .27352628111839,
    .33670437335968,
    .25623551011086,
    .28701293468475,
    .315819054842,
    .3238864839077,
    .35844340920448,
    .34399557113647,
    .40348997712135,
    .39373970031738,
    .4022718667984,
    .46476069092751,
    .45762005448341,
    .46842387318611,
    .50536489486694,
    .52051961421967,
    .47866532206535,
    .50378143787384,
    .50863671302795,
    .4302790760994,
    .49568024277687,
    .44652271270752,
    .43774726986885,
    .43010330200195,
    .42344436049461,
    .44517293572426,
    .47460499405861,
    .62086409330368,
    .52550911903381,
    .77532315254211,
    .78466820716858,
    .85438597202301,
    .87056696414948,
    1.0393311977386,
    .99110960960388,
    .85202795267105,
    .91560190916061,
    .89238166809082,
    .88917690515518,
    .72121334075928,
    .84221452474594,
    .8454754948616,
    .82078683376312,
    .95394861698151,
    .84718400239944,
    .839300096035,
    .91501939296722,
    .95743554830551,
    1.0874761343002,
    1.1326615810394,
    1.1169674396515,
    1.3300451040268,
    1.4790810346603,
    1.5027786493301,
    1.7226468324661,
    1.8395622968674,
    1.5940405130386,
    1.694568157196,
    1.8241587877274,
    1.7037791013718,
    1.838702917099,
    1.7334734201431,
    1.4791669845581,
    1.3007366657257,
    1.7364456653595,
    1.2694935798645,
    .96595168113708,
    1.1405370235443,
    1.1328836679459,
    1.1091921329498,
    1.171138882637,
    1.1465038061142,
    1.0319484472275,
    1.055313706398,
    .93150246143341,
    1.0844472646713,
    .93333613872528,
    .93137633800507,
    1.0778160095215,
    .38748729228973,
    .77933365106583,
    .75266307592392,
    .88410103321075,
    .94100385904312,
    .91849637031555,
    .96046274900436,
    .92494148015976,
    .98310285806656,
    1.0272513628006,
    1.0762135982513,
    1.0743116140366,
    1.254854798317,
    1.1723403930664,
    1.0479376316071,
    1.3550333976746,
    1.2255589962006,
    1.2870025634766,
    1.6643482446671,
    1.3312928676605,
    1.0657893419266,
    1.1804157495499,
    1.1335761547089,
    1.137326002121,
    1.1235628128052,
    1.1115798950195,
    1.1286649703979,
    1.0989991426468,
    1.0626485347748,
    .96542054414749,
    1.0419135093689,
    .93033194541931,
    .95628559589386,
    1.027433514595,
    .98328214883804,
    1.0063992738724,
    1.0645687580109,
    .94354963302612,
    .95077443122864,
    1.0226324796677,
    1.089217543602,
    .97552293539047,
    1.0441918373108,
    1.052937746048,
    .86785578727722,
    .82579529285431,
    .95432937145233,
    .79897737503052,
    .68320548534393,
    .85365778207779,
    .78336101770401,
    .80072748661041,
    .9089440703392,
    .82500487565994,
    .98515397310257,
    .96745657920837,
    1.0962044000626,
    1.195325255394,
    1.0824474096298,
    1.2239117622375,
    1.0142554044724,
    1.0399018526077,
    .80796521902084,
    .7145761847496,
    1.0631860494614,
    .86374056339264,
    .98086261749268,
    1.0528303384781,
    .86123734712601,
    .80300676822662,
    .96200370788574,
    1.0364016294479,
    .98456978797913,
    1.1556725502014,
    1.2025715112686,
    1.0507286787033,
    1.312912106514,
    1.0682457685471,
    2.0334177017212,
    1.0775905847549,
    1.2798084020615,
    1.461397767067,
    .72960823774338,
    1.2498733997345,
    1.466894865036,
    1.286082983017,
    1.3903408050537,
    1.8483582735062,
    1.4685434103012,
    2.3107523918152,
    .7711226940155,
    -.31598940491676,
    .68151205778122,
    1.0212944746017])

y = np.array([
    np.nan,
    29.704284667969,
    29.712087631226,
    29.881610870361,
    29.820302963257,
    29.992294311523,
    29.934322357178,
    30.155170440674,
    30.200632095337,
    30.117542266846,
    30.24044418335,
    30.274082183838,
    30.319667816162,
    30.507436752319,
    30.470119476318,
    30.657470703125,
    30.68822479248,
    30.714269638062,
    30.962333679199,
    30.985248565674,
    31.204275131226,
    31.16787147522,
    31.244613647461,
    31.348531723022,
    31.523355484009,
    31.609535217285,
    31.835243225098,
    31.874824523926,
    32.144504547119,
    32.5986328125,
    32.723526000977,
    33.186702728271,
    33.156238555908,
    33.387012481689,
    33.7158203125,
    34.023887634277,
    34.458442687988,
    34.743995666504,
    35.303489685059,
    35.693740844727,
    36.102272033691,
    36.764759063721,
    37.257617950439,
    37.768424987793,
    38.405364990234,
    39.020519256592,
    39.378665924072,
    39.903781890869,
    40.408638000488,
    40.530277252197,
    41.095680236816,
    41.346523284912,
    41.637748718262,
    41.930103302002,
    42.223442077637,
    42.645172119141,
    43.174606323242,
    44.320865631104,
    44.725509643555,
    46.37532043457,
    47.584667205811,
    48.954383850098,
    50.170566558838,
    52.039329528809,
    53.291107177734,
    53.852027893066,
    54.915603637695,
    55.792385101318,
    56.6891746521,
    56.821212768555,
    57.842212677002,
    58.745475769043,
    59.5207862854,
    60.953948974609,
    61.6471824646,
    62.439296722412,
    63.615020751953,
    64.857437133789,
    66.587478637695,
    68.23265838623,
    69.616966247559,
    71.930046081543,
    74.479080200195,