statsmodels.stats.diagnostic.linear_rainbow¶
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statsmodels.stats.diagnostic.
linear_rainbow
(res, frac=0.5, order_by=None, use_distance=False, center=None)[source]¶ Rainbow test for linearity
The null hypothesis is the fit of the model using full sample is the same as using a central subset. The alternative is that the fits are difference. The rainbow test has power against many different forms of nonlinearity.
- Parameters
res : RegressionResults
A results instance from a linear regression.
frac : float, default 0.5
The fraction of the data to include in the center model.
order_by : {ndarray, str, List[str]}, default None
If an ndarray, the values in the array are used to sort the observations. If a string or a list of strings, these are interpreted as column name(s) which are then used to lexicographically sort the data.
use_distance : bool, default False
Flag indicating whether data should be ordered by the Mahalanobis distance to the center.
center : {float, int}, default None
If a float, the value must be in [0, 1] and the center is center * nobs of the ordered data. If an integer, must be in [0, nobs) and is interpreted as the observation of the ordered data to use.
- Returns
fstat : float
The test statistic based on the F test.
pvalue : float
The pvalue of the test.
Notes
This test assumes residuals are homoskedastic and may reject a correct linear specification if the residuals are heteroskedastic.