Hazard function estimation with nonnegative “wavelets”

Wavelets have been successfully used for nonparametric function estimation, but for density and hazard functions, estimators must be nonnegative. In this paper, we develop a quasi-continuous nonnegative “wavelet” basis from Daubechies wavelets with good approximation properties. Using this basis, we develop a Bayesian nonparametric estimator of the hazard function for randomly right-censored data.

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Year of publication:	2013
Authors:	Angers, Jean-Francois ; MacGibbon, Brenda
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 83.2013, 4, p. 969-978
Publisher:	Elsevier
Subject:	Bayesian hierarchical model \| Dirichlet priors \| Density and distribution function estimation \| Wavelets

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011040032