Semiparametric estimation in single index Poisson regression : a practical approach.

In a single index Poisson regression model with unknown link function, the index parameter can be root-n consistently estimated by the method of pseudo maximumum likelihood. In this paper, we study, by simulation arguments, the practical validity of the asymptotic behavior of the pseudo maximum likelihood index estimator and of some associated cross-validation bandwidths. A robust practical rule for implementing the pseudo maximum likelihood estimation method is suggested, which uses the bootstrap for estimating the variance of the index estimator and a variant of bagging for numerically stabilizing its variance. Our method gives reasonable results even for moderate sized samples thus it can be used for doing statistical inference in practical situations. The procedure is illustrated through a real data example.

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Document type	Document de travail (Working Paper)
Access type	Accès libre
Publication date	2001
Language	Anglais
Number of pages	28 pages
Collection	STAT Discussion Papers - 0123
Affiliations	UCL - EUEN/STAT - Institut de statistique CREST-ENSAE
Keywords	Single index models ; Poisson regression ; kernel estimation ; bandwidth selection ; bootstrap
Links	http://sites.uclouvain.be/IAP-Stat-Phase-V-VI/ISBApub/ISBAdp.html#2001 http://hdl.handle.net/2078.1/121506[Handle]

See also
	[boreal:41718]	Semiparametric estimation in single index Poisson regression: a practical approach