import numpy as np

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, 
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                        .00226345462929, 
                       -.00395404914463, 
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                        .00039879711931, 
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                       -.00685704952799, 
                        .00363586332269, 
                        .00751765532203, 
                        .00008982556101, 
                        -.0036338799176, 
                       -.00018629958479, 
                        .00039879711931, 
                        .00008982556101, 
                        .00077550533053]).reshape(5,5)

xb = np.array([ .72428566217422, 
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y = np.array([np.nan, 
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resid = np.array([np.nan, 
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yr = np.array([np.nan, 
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               -4.0317454338074, 
               -5.4861345291138, 
                .81299871206284, 
                1.1164767742157, 
                .89470589160919])

mse = np.array([ 1.1115040779114, 
                 .69814515113831, 
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stdp = np.array([ .72428566217422, 
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                  .96745657920837, 
                  1.0962044000626, 
                   1.195325255394, 
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                  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])

icstats = np.array([             202, 
                    np.nan, 
                    -240.29558272688, 
                                   5, 
                     490.59116545376, 
                     507.13250394077])

class Bunch(dict):
    def __init__(self, **kw):
        dict.__init__(self, kw)
        self.__dict__  = self


results = Bunch(llf=llf, nobs=nobs, k=k, k_exog=k_exog, sigma=sigma, chi2=chi2, df_model=df_model, k_ar=k_ar, k_ma=k_ma, params=params, cov_params=cov_params, xb=xb, y=y, resid=resid, yr=yr, mse=mse, stdp=stdp, icstats=icstats, )