Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1146042 | Journal of Multivariate Analysis | 2011 | 20 Pages |
Abstract
In this paper we define a new nonlinear wavelet-based estimator of conditional density function for a random left truncation and right censoring model. We provide an asymptotic expression for the mean integrated squared error (MISE) of the estimator. It is assumed that the lifetime observations form a stationary αα-mixing sequence. Unlike for kernel estimators, the MISE expression of the wavelet-based estimators is not affected by the presence of discontinuities in the curves. Also, asymptotic normality of the estimator is established.
Related Topics
Physical Sciences and Engineering
Mathematics
Numerical Analysis
Authors
Han-Ying Liang, Jacobo de Uña-Álvarez,