import numpy as np

llf = np.array([-241.75576160303])

nobs = np.array([             202])

k = np.array([               4])

k_exog = np.array([               1])

sigma = np.array([ .79987660416529])

chi2 = np.array([ 342.91413339514])

df_model = np.array([               2])

k_ar = np.array([               1])

k_ma = np.array([               1])

params = np.array([ .88084748605315, 
                    .93989719451385, 
                    -.7709851377434, 
                    .79987660416529])

cov_params = np.array([ .15020189867396, 
                       -.01642122563089, 
                        .01456018801049, 
                       -.00156750041014, 
                       -.01642122563089, 
                         .0032067778715, 
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                        .01456018801049, 
                       -.00350387326241, 
                        .00480028434835, 
                       -.00068065418463, 
                       -.00156750041014, 
                        .00059634328354, 
                       -.00068065418463, 
                        .00029322997097]).reshape(4,4)

xb = np.array([ .88084751367569, 
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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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               -3.7851057052612, 
               -6.0686569213867, 
                .19684991240501, 
                1.4296782016754, 
                1.2753949165344])

mse = np.array([  .7963672876358, 
                  .7963672876358, 
                 .71457105875015, 
                 .67959600687027, 
                 .66207146644592, 
                 .65259438753128, 
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stdp = np.array([ .88084751367569, 
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                  .98641014099121, 
                  1.0837067365646, 
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                  1.2460317611694, 
                  1.1487410068512, 
                  1.1075156927109, 
                  .94060403108597, 
                   .7950227856636, 
                  .93615245819092, 
                  .89293897151947, 
                  .94407802820206, 
                  1.0172899961472, 
                  .93860250711441, 
                  .86104601621628, 
                  .91948908567429, 
                  .99833220243454, 
                   1.008442401886, 
                  1.1175880432129, 
                  1.2017351388931, 
                  1.1483734846115, 
                  1.2761443853378, 
                   1.188849568367, 
                  1.7296310663223, 
                  1.4202431440353, 
                  1.3675138950348, 
                   1.445098400116, 
                   1.031960606575, 
                  1.1313284635544, 
                  1.3214453458786, 
                  1.3112732172012, 
                   1.367110490799, 
                   1.674845457077, 
                  1.5979281663895, 
                   2.064112663269, 
                  1.3536450862885, 
                  .30015936493874, 
                  .36831066012383, 
                  .64060544967651])

icstats = np.array([             202, 
                    np.nan, 
                    -241.75576160303, 
                                   4, 
                     491.51152320605, 
                     504.74459399566])

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, )