Testing strict monotonicity in nonparametric regression
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Date
2007-02-21T14:44:43Z
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Abstract
A new test for strict monotonicity of the regression function is proposed which is based
on a composition of an estimate of the inverse of the regression function with a common
regression estimate. This composition is equal to the identity if and only if the “true”
regression function is strictly monotone, and a test based on an L2-distance is investigated.
The asymptotic normality of the corresponding test statistic is established under the null
hypothesis of strict monotonicity.
AMS Subject Classification: 62G10
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Keywords
Goodness-of-fit test, Nonparametric regression, Strictly monotone regression