A comparison of three point estimators for \(P(Y<X)\) in the normal case
type: Item
instance of: scholarly article
title: A comparison of three point estimators for \(P(Y<X)\) in the normal case
zbMATH Open document ID: 0606.62111
DOI: 10.1016/0167-9473(87)90008-9
author: Benjamin Reiser
author: Irwin Guttman
published in: Computational Statistics and Data Analysis
publication date: 1987-01-01T00:00:00Z
review text: This paper discusses point estimation for \(R=P(Y<X)\) where X and Y are independent normal variables. R can be considered to be the reliability of a system with strength X to which is applied stress Y. A predictive estimator which can be calculated from the Behrens-Fisher distribution is derived and compared with the maximum likelihood and uniformly minimum variance unbiased estimators through a simulation study.
Mathematics Subject Classification ID: 62N05
Mathematics Subject Classification ID: 62F10
zbMATH DE Number: 3980314
zbMATH Keywords: UMVUE
zbMATH Keywords: standard normal distribution
zbMATH Keywords: reliability
zbMATH Keywords: predictive estimator
zbMATH Keywords: Behrens-Fisher distribution
zbMATH Keywords: maximum likelihood
zbMATH Keywords: uniformly minimum variance unbiased estimators
zbMATH Keywords: simulation study
MaRDI profile type: Publication
full work available at URL: 0167-9473(87)90008-9
OpenAlex ID: W2084744038
Wikidata QID: Q57090343
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description: scientific article; zbMATH DE number 3980314