statsmodels.stats.diagnostic.het_goldfeldquandt¶
- statsmodels.stats.diagnostic.het_goldfeldquandt(y, x, idx=None, split=None, drop=None, alternative='increasing', store=False)[source]¶
Goldfeld-Quandt 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”, “two-sided”}
The default is increasing. This specifies the alternative for the p-value calculation.
- storebool,
default
False
Flag indicating to return the regression results
- Returns:
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)