A New Application of Generalized Linear Failure Rate Distribution in Agriculture Using Ranked Set Sampling

Abstract

This article deals with perform inferences about stress–strength model R, =, P, [, Y, <, X, ], , , when X and Y are two independent random variables with generalized linear failure rate distribution (GLFRD) with the same and known scale parameters but not identically shaped parameters. In the literature, estimators based on simple random sample (SRS) are widely used in estimating stress–strength model. But in the resent years, ranked set sampling (RSS) has become popular in performing statistical inference. Therefore, the estimator of R based on RSS using maximum likelihood and modified maximum likelihood are obtained. Monte Carlo simulation study is performed to compare the estimators of R are obtained using RSS and SRS. Finally, agriculture application is presented.