import numpy as np

from statsmodels.tools.tools import Bunch

llf = np.array([-239.75290561974])

nobs = np.array([202])

k = np.array([4])

k_exog = np.array([1])

sigma = np.array([.79291203639424])

chi2 = np.array([35036.682546665])

df_model = np.array([3])

k_ar = np.array([1])

k_ma = np.array([2])

params = np.array([
    .99954097483478,
    -.69022779461512,
    -.20477682541104,
    .62870949745886])

cov_params = np.array([
    .00007344276568,
    -.00016074342677,
    -.00018478942445,
    8.040251506e-06,
    -.00016074342677,
    .00094099304774,
    .00017233777676,
    -.0000145011098,
    -.00018478942445,
    .00017233777676,
    .00103352686916,
    .00030686101903,
    8.040251506e-06,
    -.0000145011098,
    .00030686101903,
    .00067796985496]).reshape(4, 4)

xb = np.array([
    0,
    0,
    .05104803293943,
    .06663129478693,
    .02164618112147,
    .0773858949542,
    .02606418170035,
    .09391833096743,
    .05710592120886,
    .03083370067179,
    .07319989800453,
    .05287836492062,
    .05776296555996,
    .09105986356735,
    .04293738678098,
    .09576436132193,
    .06068528071046,
    .06157376244664,
    .11172580718994,
    .06527806818485,
    .11443704366684,
    .05653077363968,
    .08205550909042,
    .08481238037348,
    .10436166077852,
    .0875685736537,
    .12320486456156,
    .08366665989161,
    .13979130983353,
    .1902572363615,
    .1306214183569,
    .21803694963455,
    .11079790443182,
    .17274764180183,
    .1937662512064,
    .20047917962074,
    .24034893512726,
    .21783453226089,
    .29279819130898,
    .26804205775261,
    .28678458929062,
    .35651323199272,
    .33659368753433,
    .35760068893433,
    .39895334839821,
    .41131839156151,
    .36645981669426,
    .40991494059563,
    .41024547815323,
    .32657703757286,
    .42312324047089,
    .34933325648308,
    .35912537574768,
    .35077446699142,
    .34701564908028,
    .37364318966866,
    .40170526504517,
    .56070649623871,
    .41915491223335,
    .73478156328201,
    .67748892307281,
    .7744625210762,
    .77825599908829,
    .97586625814438,
    .88692498207092,
    .76232481002808,
    .87376874685287,
    .83281141519547,
    .84783887863159,
    .66423743963242,
    .84904235601425,
    .81613594293594,
    .80033475160599,
    .95782464742661,
    .80624777078629,
    .83626395463943,
    .91873735189438,
    .95130664110184,
    1.0939226150513,
    1.1171194314957,
    1.1004731655121,
    1.3512066602707,
    1.4703129529953,
    1.4805699586868,
    1.7385860681534,
    1.8268398046494,
    1.5489361286163,
    1.7446503639221,
    1.864644408226,
    1.7200467586517,
    1.9223358631134,
    1.775306224823,
    1.5392524003983,
    1.4067870378494,
    1.9366238117218,
    1.2984343767166,
    1.1080636978149,
    1.3500427007675,
    1.2837564945221,
    1.2670782804489,
    1.3347851037979,
    1.2857422828674,
    1.1625040769577,
    1.2111755609512,
    1.0548515319824,
    1.2553508281708,
    1.0327949523926,
    1.0740388631821,
    1.222040772438,
    .40555971860886,
    1.0233588218689,
    .84209614992142,
    1.0186324119568,
    1.0319027900696,
    .99487775564194,
    1.0439211130142,
    .98785293102264,
    1.0620124340057,
    1.0916963815689,
    1.1378232240677,
    1.1243290901184,
    1.3305295705795,
    1.1925677061081,
    1.0872994661331,
    1.4599523544312,
    1.2333589792252,
    1.3584797382355,
    1.7595859766006,
    1.3009568452835,
    1.1157965660095,
    1.2948887348175,
    1.2063180208206,
    1.2332669496536,
    1.2132470607758,
    1.2049551010132,
    1.2260574102402,
    1.1875206232071,
    1.1547852754593,
    1.0519831180573,
    1.1594845056534,
    1.0069926977158,
    1.0675266981125,
    1.1299223899841,
    1.0620901584625,
    1.0999356508255,
    1.1535499095917,
    1.0026944875717,
    1.0428657531738,
    1.1120204925537,
    1.1684119701385,
    1.0258769989014,
    1.1342295408249,
    1.1183958053589,
    .91313683986664,
    .91156214475632,
    1.0540328025818,
    .84359037876129,
    .75758427381516,
    .96401190757751,
    .83226495981216,
    .8759680390358,
    .98239886760712,
    .85917687416077,
    1.0634194612503,
    .99442666769028,
    1.153311252594,
    1.2288066148758,
    1.0869039297104,
    1.281947016716,
    1.0067318677902,
    1.1028815507889,
    .82448446750641,
    .78489726781845,
    1.1850204467773,
    .86753690242767,
    1.0692945718765,
    1.1030179262161,
    .8791960477829,
    .86451041698456,
    1.0455346107483,
    1.085998415947,
    1.0172398090363,
    1.2250980138779,
    1.2316122055054,
    1.062157869339,
    1.3991860151291,
    1.0520887374878,
    2.2203133106232,
    .88833123445511,
    1.4289729595184,
    1.5206423997879,
    .68520504236221,
    1.4659557342529,
    1.5350053310394,
    1.3178979158401,
    1.4888265132904,
    1.9698411226273,
    1.4406447410583,
    2.517040014267,
    .55537897348404,
    -.20722626149654,
    1.0899519920349,
    1.164245724678])

y = np.array([
    np.nan,
    28.979999542236,
    29.201047897339,
    29.416631698608,
    29.391647338867,
    29.617385864258,
    29.576063156128,
    29.84391784668,
    29.897106170654,
    29.84083366394,
    29.993200302124,
    30.032876968384,
    30.097763061523,
    30.3010597229,
    30.262937545776,
    30.475763320923,
    30.500686645508,
    30.541572570801,
    30.801725387573,
    30.815279006958,
    31.054437637329,
    31.006530761719,
    31.102056503296,
    31.20481300354,
    31.384363174438,
    31.467567443848,
    31.703205108643,
    31.733665466309,
    32.019790649414,
    32.47025680542,
    32.580623626709,
    33.068035125732,
    33.010799407959,
    33.272747039795,
    33.593769073486,
    33.900478363037,
    34.340347290039,
    34.617835998535,
    35.192798614502,
    35.568042755127,
    35.986785888672,
    36.656513214111,
    37.13659286499,
    37.657600402832,
    38.29895401001,
    38.911319732666,
    39.266460418701,
    39.809917449951,
    40.310245513916,
    40.426574707031,
    41.023120880127,
    41.249336242676,
    41.559127807617,
    41.850772857666,
    42.14701461792,
    42.573642730713,
    43.101707458496,
    44.260707855225,
    44.619155883789,
    46.334781646729,
    47.477489471436,
    48.874462127686,
    50.078254699707,
    51.9758644104,
    53.186923980713,
    53.762325286865,
    54.873767852783,
    55.732814788818,
    56.647838592529,
    56.764236450195,
    57.849040985107,
    58.716136932373,
    59.500335693359,
    60.957824707031,
    61.606246948242,
    62.436264038086,
    63.61873626709,
    64.85131072998,
    66.593925476074,
    68.21711730957,
    69.600471496582,
    71.951202392578,
    74.470314025879,
    76.680564880371,
    79.738586425781,
    82.726844787598,
    84.148933410645,
    86.444648742676,
    89.064643859863,
    90.820045471191,
    93.422332763672,
    95.175308227539,
    95.939254760742,