Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1152136 | Statistics & Probability Letters | 2013 | 10 Pages |
Abstract
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.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Jean-Francois Angers, Brenda MacGibbon,