A consistent nonparametric test of the convexity of regression based on least squares splines

This paper provides a test of convexity of a regression function. This test is based on the least squares splines. The test statistic is shown to be asymptotically of size equal to the nominal level, while diverging to infinity if the convexity is misspecified. Therefore, the test is consistent against all deviations from the null hypothesis.

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Year of publication:	1998
Authors:	Diack, Cheikh A. T.
Publisher:	Berlin : Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes
Subject:	least squares estimator \| test of convexity \| Likelihood ratio test \| convex cone

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Series:	SFB 373 Discussion Paper ; 1998,44
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	721976409 [GVK] hdl:10419/61284 [Handle] RePEc:zbw:sfb373:199844 [RePEc]
Source:	EconStor

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010309896