학술논문

Estimation of P(X > Y) when X and Y are dependent random variables using different bivariate sampling schemes
Document Type
Academic Journal
Source
CSAM(Communications for Statistical Applications and Methods). 2016-09 23(5):385-397
Subject
bias
bivariate ranked set sampling
bivariate simple random sampling
empirical and kernel estimation
mean square error
reliability
Language
Korean
Abstract
The stress-strength models have been intensively investigated in the literature in regards of estimating the reliability = P (X > Y) using parametric and nonparametric approaches under different sampling schemes when X and Y are independent random variables. In this paper, we consider the problem of estimating when (X; Y) are dependent random variables with a bivariate underlying distribution. The empirical and kernel estimates of = P (X > Y), based on bivariate ranked set sampling (BVRSS) are considered, when (X; Y) are paired dependent continuous random variables. The estimators obtained are compared to their counterpart, bivariate simple random sampling (BVSRS), via the bias and mean square error (MSE). We demonstrate that the suggested estimators based on BVRSS are more efficient than those based on BVSRS. A simulation study is conducted to gain insight into the performance of the proposed estimators. A real data example is provided to illustrate the process.

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