6.3.6. statsmodels.sandbox.distributions.gof_new¶
More Goodness of fit tests
contains
GOF : 1 sample gof tests based on Stephens 1970, plus AD A^2 bootstrap : vectorized bootstrap p-values for gof test with fitted parameters
Created : 2011-05-21 Author : Josef Perktold
parts based on ks_2samp and kstest from scipy.stats.stats (license: Scipy BSD, but were completely rewritten by Josef Perktold)
6.3.6.1. References¶
6.3.6.2. Functions¶
a_st70_upp(stat, nobs) |
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asquare(cdfvals[, axis]) |
vectorized Anderson Darling A^2, Stephens 1974 |
bootstrap(distr[, args, nobs, nrep, value, ...]) |
Monte Carlo (or parametric bootstrap) p-values for gof |
bootstrap2(value, distr[, args, nobs, nrep]) |
Monte Carlo (or parametric bootstrap) p-values for gof |
d_st70_upp(stat, nobs) |
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dminus_st70_upp(stat, nobs) |
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dplus_st70_upp(stat, nobs) |
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gof_mc(randfn, distr[, nobs]) |
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ks_2samp(data1, data2) |
Computes the Kolmogorov-Smirnof statistic on 2 samples. |
kstest(rvs, cdf[, args, N, alternative, mode]) |
Perform the Kolmogorov-Smirnov test for goodness of fit |
pval_kstest_approx(D, N) |
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usqu_st70_upp(stat, nobs) |
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v_st70_upp(stat, nobs) |
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wsqu_st70_upp(stat, nobs) |