statsmodels.stats.gof.gof_binning_discrete¶
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statsmodels.stats.gof.
gof_binning_discrete
(rvs, distfn, arg, nsupp=20)[source]¶ get bins for chisquare type gof tests for a discrete distribution
Parameters: rvs : ndarray
sample data
distname : str
name of distribution function
arg : sequence
parameters of distribution
nsupp : int
number of bins. The algorithm tries to find bins with equal weights. depending on the distribution, the actual number of bins can be smaller.
Returns: freq : ndarray
empirical frequencies for sample; not normalized, adds up to sample size
expfreq : ndarray
theoretical frequencies according to distribution
histsupp : ndarray
bin boundaries for histogram, (added 1e-8 for numerical robustness)
Notes
The results can be used for a chisquare test
(chis,pval) = stats.chisquare(freq, expfreq)
originally written for scipy.stats test suite, still needs to be checked for standalone usage, insufficient input checking may not run yet (after copy/paste)
- refactor: maybe a class, check returns, or separate binning from
- test results
- todo :
- optimal number of bins ? (check easyfit), recommendation in literature at least 5 expected observations in each bin