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