statsmodels.stats.diagnostic.het_goldfeldquandt¶

statsmodels.stats.diagnostic.
het_goldfeldquandt
(y, x, idx=None, split=None, drop=None, alternative='increasing', store=False)[source]¶ GoldfeldQuandt homoskedasticity test.
This test examines whether the residual variance is the same in 2 subsamples.
 Parameters
 yarray_like
endogenous variable
 xarray_like
exogenous variable, regressors
 idx
int
,default
None
column index of variable according to which observations are sorted for the split
 split{
int
,float
},default
None
If an integer, this is the index at which sample is split. If a float in 0<split<1 then split is interpreted as fraction of the observations in the first sample. If None, uses nobs//2.
 drop{
int
,float
},default
None
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:]
 alternative{“increasing”, “decreasing”, “twosided”}
The default is increasing. This specifies the alternative for the pvalue calculation.
 storebool,
default
False
Flag indicating to return the regression results
 Returns
Notes
The Null hypothesis is that the variance in the two subsamples 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 twosided.
Results are identical R, but the drop option is defined differently. (sorting by idx not tested yet)