statsmodels.stats.diagnostic.HetGoldfeldQuandt
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class statsmodels.stats.diagnostic.HetGoldfeldQuandt
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test whether variance is the same in 2 subsamples
Parameters: y : array_like
endogenous variable
x : array_like
exogenous variable, regressors
idx : integer
column index of variable according to which observations are sorted for the split
split : None 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
drop : None, 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:]
alternative : string, ?increasing?, ?decreasing? or ?two-sided?
default is increasing. This specifies the alternative for the p-value calculation.
Returns: (fval, pval) or res :
fval : float
value of the F-statistic
pval : float
p-value of the hypothesis that the variance in one subsample is larger than in the other subsample
res : instance 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
run
(y, x[, idx, split, drop, alternative, ...])see class docstring
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