import numpy as np

llf = np.array([-240.21658671417])

nobs = np.array([             202])

k = np.array([               4])

k_exog = np.array([               1])

sigma = np.array([ .79473430527544])

chi2 = np.array([ 54633.096432541])

df_model = np.array([               3])

k_ar = np.array([               2])

k_ma = np.array([               1])

params = np.array([ 1.1970355174119, 
                   -.19724105359909, 
                   -.91770441432171, 
                    .63160261598163])

cov_params = np.array([ .00182362158934, 
                       -.00163271308366, 
                       -.00140915922719, 
                       -.00044400541718, 
                       -.00163271308366, 
                        .00148731108625, 
                        .00117094734518, 
                        .00044939207189, 
                       -.00140915922719, 
                        .00117094734518, 
                        .00181742086472, 
                        .00032737864417, 
                       -.00044400541718, 
                        .00044939207189, 
                        .00032737864417, 
                        .00071193796554]).reshape(4,4)

xb = np.array([               0, 
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                1.1858888864517])

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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               -5.5225644111633, 
                .73351317644119, 
                .94620555639267, 
                .73011147975922])

mse = np.array([ 1.1635265350342, 
                 .70545583963394, 
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stdp = np.array([               0, 
                                0, 
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                  .93606770038605, 
                  .85732334852219, 
                  .87216699123383, 
                  .97779452800751, 
                  .88410341739655, 
                  1.0446182489395, 
                  1.0177079439163, 
                   1.144193649292, 
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                  1.2619564533234, 
                  1.0462523698807, 
                  1.0816910266876, 
                  .85130125284195, 
                  .76972281932831, 
                  1.1335872411728, 
                  .92024201154709, 
                  1.0416384935379, 
                  1.1102936267853, 
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                  .85678082704544, 
                   1.022847533226, 
                  1.0930491685867, 
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                  1.2070096731186, 
                  1.2472279071808, 
                  1.0886085033417, 
                  1.3604420423508, 
                  1.1053978204727, 
                  2.0939025878906, 
                  1.0898643732071, 
                  1.3238569498062, 
                  1.5171576738358, 
                  .77435439825058, 
                  1.3360253572464, 
                  1.5512014627457, 
                  1.3569095134735, 
                  1.4669530391693, 
                  1.9312930107117, 
                    1.52878677845, 
                  2.3952746391296, 
                  .80755305290222, 
                  -.2365039139986, 
                  .85178333520889, 
                  1.1858888864517])

icstats = np.array([             202, 
                    np.nan, 
                    -240.21658671417, 
                                   4, 
                     488.43317342834, 
                     501.66624421795])

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, )