A nonparametric test of the non-convexity of regression

This paper proposes a nonparametric test of the non-convexity of a smooth regression function based on least squares or hybrid splines. By a simple formulation of the convexity hypothesis in the class of all polynomial cubic splines, we build a test which has an asymptotic size equal to the nominal level. It is shown that the test is consistent and is robust to nonnormality. The behavior of the test under the local alternatives is studied.

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Year of publication:	1998
Authors:	Diack, Cheikh A. T. ; Thomas-Agnan, Christine
Publisher:	Berlin : Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes
Subject:	least squares estimator \| test of convexity \| B-splines \| modulus of continuity

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Series:	SFB 373 Discussion Paper ; 1998,43
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	721976123 [GVK] hdl:10419/61308 [Handle] RePEc:zbw:sfb373:199843 [RePEc]
Source:	EconStor

Persistent link: https://www.econbiz.de/10010309920