71 lines
1.9 KiB
Python
71 lines
1.9 KiB
Python
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"""
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Created on Fri Sep 30 15:20:45 2011
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@author: josef
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"""
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from statsmodels.compat.python import lrange
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import numpy as np
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from scipy import stats
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from statsmodels.sandbox.tools.mctools import StatTestMC
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from statsmodels.stats.diagnostic import acorr_ljungbox
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from statsmodels.tsa.stattools import adfuller
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def normalnoisesim(nobs=500, loc=0.0):
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return (loc+np.random.randn(nobs))
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def lb(x):
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s,p = acorr_ljungbox(x, lags=4)
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return np.r_[s, p]
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mc1 = StatTestMC(normalnoisesim, lb)
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mc1.run(5000, statindices=lrange(4))
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print(mc1.summary_quantiles([1,2,3], stats.chi2([2,3,4]).ppf,
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varnames=['lag 1', 'lag 2', 'lag 3'],
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title='acorr_ljungbox'))
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print('\n\n')
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frac = [0.01, 0.025, 0.05, 0.1, 0.975]
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crit = stats.chi2([2,3,4]).ppf(np.atleast_2d(frac).T)
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print(mc1.summary_cdf([1,2,3], frac, crit,
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varnames=['lag 1', 'lag 2', 'lag 3'],
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title='acorr_ljungbox'))
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print(mc1.cdf(crit, [1,2,3])[1])
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#----------------------
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def randwalksim(nobs=500, drift=0.0):
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return (drift+np.random.randn(nobs)).cumsum()
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def adf20(x):
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return adfuller(x, 2, regression="n", autolag=None)
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print(adf20(np.random.randn(100)))
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mc2 = StatTestMC(randwalksim, adf20)
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mc2.run(10000, statindices=[0,1])
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frac = [0.01, 0.05, 0.1]
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#bug
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crit = np.array([-3.4996365338407074, -2.8918307730370025, -2.5829283377617176])[:,None]
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print(mc2.summary_cdf([0], frac, crit,
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varnames=['adf'],
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title='adf'))
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#bug
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#crit2 = np.column_stack((crit, frac))
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#print mc2.summary_cdf([0, 1], frac, crit,
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# varnames=['adf'],
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# title='adf')
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print(mc2.quantiles([0]))
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print(mc2.cdf(crit, [0]))
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doplot=1
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if doplot:
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import matplotlib.pyplot as plt
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mc1.plot_hist([3],stats.chi2([4]).pdf)
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plt.title('acorr_ljungbox - MC versus chi2')
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plt.show()
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