Heteroscedastic Deconvolution of P(X<Y) with Compactly Supported Error Densities

We deal with the problem of the nonparametric estimation of P X < Y which is also known as the stress–strength model problem when both X and Y are observed with additional errors. We provide the convergence rate for the suggested estimator and give a lower bound in the case that the error random...

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Bibliographic Details
Published inJournal of statistical theory and practice Vol. 13; no. 3
Main Authors Trong, Dang Duc, Nguyen, Ton That Quang, Lan, Nguyen Nhu
Format Journal Article
LanguageEnglish
Published Cham Springer International Publishing 01.09.2019
Subjects
Mathematics and Statistics
Original Article
Probability Theory and Stochastic Processes
Statistical Theory and Methods
Statistics
62G05
Convergence rate
Deconvolution
62G99
Heteroscedastic
Estimator
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Summary:We deal with the problem of the nonparametric estimation of P X < Y which is also known as the stress–strength model problem when both X and Y are observed with additional errors. We provide the convergence rate for the suggested estimator and give a lower bound in the case that the error random variables have different distributions. Some numerical results are also presented.
ISSN:1559-8608
1559-8616
DOI:10.1007/s42519-019-0050-y