Testing monotonicity of regression functions - an empirical process approach
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Date
2010-04-12T08:41:58Z
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Abstract
We propose several new tests for monotonicity of regression functions based on
different empirical processes of residuals. The residuals are obtained from recently
developed simple kernel based estimators for increasing regression functions based on
increasing rearrangements of unconstrained nonparametric estimators. The test statistics
are estimated distance measures between the regression function and its increasing
rearrangement. We discuss the asymptotic distributions, consistency, and small sample
performances of the tests. AMS Classification: 62G10, 62G08, 62G30
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Keywords
Kolmogorov-Smirnov test, Model test, Monotone rearrangement, Nonparametric regression, Residual process