3.8.6.3.7. statsmodels.nonparametric.kernel_regression.TestRegCoefD¶
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class
statsmodels.nonparametric.kernel_regression.TestRegCoefD(model, test_vars, nboot=400, nested_res=400, pivot=False)[source]¶ Significance test for the categorical variables in a nonparametric regression.
Parameters: model: Instance of KernelReg class
This is the nonparametric regression model whose elements are tested for significance.
test_vars: tuple, list of one element
index of position of the discrete variable to be tested for significance. E.g. (3) tests variable at position 3 for significance.
nboot: int
Number of bootstrap samples used to determine the distribution of the test statistic in a finite sample. Default is 400
Notes
This class currently doesn’t allow joint hypothesis. Only one variable can be tested at a time
References
See [9] and chapter 12 in [1].
Attributes
sig: str The significance level of the variable(s) tested “Not Significant”: Not significant at the 90% confidence level Fails to reject the null “*”: Significant at the 90% confidence level “**”: Significant at the 95% confidence level “***”: Significant at the 99% confidence level -
__init__(model, test_vars, nboot=400, nested_res=400, pivot=False)¶
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