A generalized reflection method for kernel distribution and hazard functions estimation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F11%3A00052529" target="_blank" >RIV/00216224:14310/11:00052529 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
A generalized reflection method for kernel distribution and hazard functions estimation
Original language description
In this paper we focus on kernel estimates of cumulative distribution and hazard functions (rates) when the observed random variables are nonnegative. It is well known that kernel distribution estimators are not consistent when estimating a distributionfunction near the point x=0. This fact is rather visible in many applications, for example in kernel ROC curve estimation (Kolacek and Karunamuni (2009)). In order to avoid this problem we propose a bias reducing technique that is a kind of generalized reflection method. Our method is based on ideas of Karunamuni and Alberts (2005) and Zhang et al. (1999) developed for boundary correction in kernel density estimation. The proposed estimators are compared with the traditional kernel estimator and with the estimator based on ``classical" reflection method using simulation studies.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BA - General mathematics
OECD FORD branch
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Project
<a href="/en/project/LC06024" target="_blank" >LC06024: Jaroslav Hájek Center for Theoretical and Applied Statistics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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