import numpy as np

from statsmodels.tools.tools import Bunch

llf = np.array([-240.79351748413])

nobs = np.array([202])

k = np.array([4])

k_exog = np.array([1])

sigma = np.array([.79349479007541])

chi2 = np.array([31643.977146904])

df_model = np.array([3])

k_ar = np.array([1])

k_ma = np.array([2])

params = np.array([
    .99502750401315,
    -.68630179255403,
    -.19840894739396,
    .79349479007541])

cov_params = np.array([
    .00010016992219,
    -.00021444523598,
    -.00023305572854,
    -6.768123591e-06,
    -.00021444523598,
    .00104186449549,
    .00023669747281,
    3.902897504e-06,
    -.00023305572854,
    .00023669747281,
    .0010810935718,
    .00020764808165,
    -6.768123591e-06,
    3.902897504e-06,
    .00020764808165,
    .0002668504612]).reshape(4, 4)

xb = np.array([
    0,
    0,
    .11361486464739,
    .14230862259865,
    .07256115227938,
    .13274206221104,
    .06747215241194,
    .13822889328003,
    .09585004299879,
    .06099047139287,
    .10120190680027,
    .07761032879353,
    .07942545413971,
    .11177492141724,
    .06088993698359,
    .11208334565163,
    .0755797252059,
    .07422959059477,
    .12350624799728,
    .07623053342104,
    .12391770631075,
    .06531815230846,
    .08897981792688,
    .09103457629681,
    .10980048775673,
    .09255626052618,
    .12732291221619,
    .08764986693859,
    .14262486994267,
    .19330270588398,
    .13410428166389,
    .2202503234148,
    .1138079687953,
    .17364008724689,
    .19471970200539,
    .20120698213577,
    .24072274565697,
    .21839858591557,
    .29251739382744,
    .26838713884354,
    .28637075424194,
    .3556769490242,
    .33624804019928,
    .35650280117989,
    .3974232673645,
    .40968126058578,
    .36446389555931,
    .40641778707504,
    .40639826655388,
    .32208651304245,
    .41636437177658,
    .34307014942169,
    .3511538207531,
    .34216031432152,
    .33759200572968,
    .36354607343674,
    .39148297905922,
    .55032896995544,
    .4113195836544,
    .7244918346405,
    .67152947187424,
    .76787060499191,
    .77276849746704,
    .96944856643677,
    .88270664215088,
    .7563271522522,
    .86404490470886,
    .82250237464905,
    .83520317077637,
    .65044301748276,
    .83044308423996,
    .79827356338501,
    .78103590011597,
    .93702721595764,
    .78709679841995,
    .81435388326645,
    .89593154191971,
    .92867535352707,
    1.0709822177887,
    1.0957812070847,
    1.0792914628983,
    1.3286831378937,
    1.4503024816513,
    1.4619816541672,
    1.7190475463867,
    1.8096150159836,
    1.5324629545212,
    1.721804857254,
    1.8408879041672,
    1.6955831050873,
    1.8928952217102,
    1.7459137439728,
    1.5055395364761,
    1.3664853572845,
    1.8893030881882,
    1.256967663765,
    1.0567245483398,
    1.2921603918076,
    1.2266329526901,
    1.2085332870483,
    1.275726556778,
    1.2278587818146,
    1.1046848297119,
    1.1517647504807,
    .99646359682083,
    1.194694519043,
    .97580307722092,
    1.0148292779922,
    1.1635760068893,
    .35167038440704,
    .95728904008865,
    .78414303064346,
    .95968008041382,
    .97746151685715,
    .94291216135025,
    .99327826499939,
    .93940645456314,
    1.013852596283,
    1.0454497337341,
    1.0929356813431,
    1.0810794830322,
    1.2874436378479,
    1.1533098220825,
    1.0470397472382,
    1.4171674251556,
    1.1959022283554,
    1.3181202411652,
    1.7197531461716,
    1.2677561044693,
    1.0768386125565,
    1.2508004903793,
    1.1625586748123,
    1.1872273683548,
    1.1668027639389,
    1.1576874256134,
    1.1782459020615,
    1.1398378610611,
    1.1065219640732,
    1.0032601356506,
    1.1087976694107,
    .95788156986237,
    1.0163568258286,
    1.079482793808,
    1.0131409168243,
    1.0506906509399,
    1.1052004098892,
    .95601671934128,
    .99452114105225,
    1.0641269683838,
    1.1217628717422,
    .98107707500458,
    1.0877858400345,
    1.0735836029053,
    .86890149116516,
    .86449563503265,
    1.0060983896255,
    .79812264442444,
    .70991164445877,
    .91461282968521,
    .78625136613846,
    .8291689157486,
    .93680161237717,
    .81633454561234,
    1.0196126699448,
    .95442569255829,
    1.1131925582886,
    1.1916073560715,
    1.05200278759,
    1.2451642751694,
    .97296446561813,
    1.0647999048233,
    .78715896606445,
    .74267995357513,
    1.1400059461594,
    .82839399576187,
    1.0262999534607,
    1.0628409385681,
    .84051495790482,
    .82304340600967,
    1.0028872489929,
    1.0457111597061,
    .97847640514374,
    1.1855980157852,
    1.195351600647,
    1.0270363092422,
    1.3610677719116,
    1.0189098119736,
    2.1800265312195,
    .86722087860107,
    1.3893752098083,
    1.4851142168045,
    .65110164880753,
    1.417050242424,
    1.4938380718231,
    1.2786860466003,
    1.446773648262,
    1.9284181594849,
    1.4071846008301,
    2.4745123386383,
    .53088372945786,
    -.25887301564217,
    1.0166070461273,
    1.1028108596802])

y = np.array([
    np.nan,
    28.979999542236,
    29.263614654541,
    29.492309570313,
    29.442562103271,
    29.672742843628,
    29.617471694946,
    29.888229370117,
    29.935850143433,
    29.870990753174,
    30.021202087402,
    30.057609558105,
    30.119426727295,
    30.321773529053,
    30.280889511108,
    30.492082595825,
    30.515581130981,
    30.554229736328,
    30.813507080078,
    30.826231002808,
    31.063919067383,
    31.015319824219,
    31.108980178833,
    31.21103477478,
    31.389801025391,
    31.472555160522,
    31.707323074341,
    31.737649917603,
    32.022624969482,
    32.473300933838,
    32.584106445313,
    33.070247650146,
    33.013809204102,
    33.273639678955,
    33.594722747803,
    33.901206970215,
    34.340721130371,
    34.61840057373,
    35.192520141602,
    35.568386077881,
    35.98637008667,
    36.65567779541,
    37.136245727539,
    37.65650177002,
    38.297424316406,
    38.909679412842,
    39.264465332031,
    39.806419372559,
    40.306400299072,
    40.42208480835,
    41.016361236572,
    41.243072509766,
    41.551155090332,
    41.84215927124,
    42.137592315674,
    42.563545227051,
    43.091484069824,
    44.250328063965,
    44.611320495605,
    46.324489593506,
    47.471527099609,
    48.867870330811,
    50.072769165039,
    51.9694480896,
    53.182704925537,
    53.756328582764,
    54.864044189453,
    55.722503662109,
    56.635204315186,
    56.750442504883,
    57.830444335938,
    58.698276519775,
    59.481037139893,
    60.937026977539,
    61.587097167969,
    62.414352416992,
    63.595932006836,
    64.828674316406,
    66.570983886719,
    68.195777893066,
    69.579292297363,
    71.928680419922,
    74.450302124023,
    76.661979675293,
    79.719047546387,
    82.709617614746,
    84.132461547852,
    86.421798706055,
    89.040885925293,
    90.79557800293,
    93.39289855957,
    95.14591217041,
    95.905540466309,