NONPARAMETRIC ESTIMATION OF HAZARD FUNCTIONS BY WAVELET METHODS
Authors:
Samuel Wu a;
Martin Wells b
| Affiliations: | a Department of Statistics, University of Florida, Gainesville, FL 32611, USA. |
| b Department of Social Statistics, Cornell University, Ithaca, NY 14853, USA. |
DOI:
10.1080/1048525031000089301
Publication Frequency:
8 issues per year
Subjects:
Mathematical Economics;
Mathematical Finance;
Medical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
Number of References: 29
Formats available:
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Abstract
This paper studies hazard rate estimation by non-linear wavelet methods in the setting of the counting process intensity model. An asymptotic formula for the mean integrated squared error (MISE) is provided. In addition, we show that the same MISE convergence result holds for hazard rates which are only piecewise smooth, in contrast to the analogous situation for kernel smoothing. Local properties, including consistency and asymptotic normality, are also established.
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| Keywords: Hazard Rate Estimation; Left Truncated And Right Censored Data; Martingales; Mean Integrated Squarred Error; Wavelet Based Estimator |
| view references (29) |

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