statsmodels.stats.diagnostic.HetGoldfeldQuandt

class statsmodels.stats.diagnostic.HetGoldfeldQuandt

test whether variance is the same in 2 subsamples

Parameters

yarray_like

endogenous variable

xarray_like

exogenous variable, regressors

idxinteger

column index of variable according to which observations are sorted for the split

splitNone or integer or float in intervall (0,1)

index at which sample is split. If 0<split<1 then split is interpreted as fraction of the observations in the first sample

dropNone, float or int

If this is not None, then observation are dropped from the middle part of the sorted series. If 0<split<1 then split is interpreted as fraction of the number of observations to be dropped. Note: Currently, observations are dropped between split and split+drop, where split and drop are the indices (given by rounding if specified as fraction). The first sample is [0:split], the second sample is [split+drop:]

alternativestring, ‘increasing’, ‘decreasing’ or ‘two-sided’

default is increasing. This specifies the alternative for the p-value calculation.

Returns

(fval, pval) or res

fvalfloat

value of the F-statistic

pvalfloat

p-value of the hypothesis that the variance in one subsample is larger than in the other subsample

resinstance of result class

The class instance is just a storage for the intermediate and final results that are calculated

Notes

The Null hypothesis is that the variance in the two sub-samples are the same. The alternative hypothesis, can be increasing, i.e. the variance in the second sample is larger than in the first, or decreasing or two-sided.

Results are identical R, but the drop option is defined differently. (sorting by idx not tested yet)

Methods

__call__(y, x[, idx, split, drop, alternative])	Call self as a function.
run(y, x[, idx, split, drop, alternative, …])	see class docstring