Improved estimators for stress-strength reliability using record ranked set sampling scheme
From MaRDI portal
Publication:5087546
DOI10.1080/03610918.2018.1468451OpenAlexW2915598196MaRDI QIDQ5087546
A. Safariyan, Mohammad Arashi, R. Arabi Belaghi
Publication date: 1 July 2022
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918.2018.1468451
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Record ranked set sampling scheme
- Estimation of \(R=P(Y<X)\) for three-parameter Weibull distribution
- Likelihood and Bayesian estimation of \(\mathrm{Pr}(X \leq Y)\) using lower record values from the generalized exponential distribution
- Improved confidence intervals for the scale parameter of Burr XII model based on record values
- Improved estimators of the distribution function based on lower record values
- Comparison of two sampling schemes for generating record-breaking data from the proportional hazard rate models
- A Distribution-Free Upper Confidence Bound for $\Pr \{Y < X\}$, Based on Independent Samples of $X$ and $Y$
- EstimatingP(Y < X) using Ranked Set Sampling in Case of the Exponential Distribution
- Performance of some new preliminary test ridge regression estimators and their properties
- Interval estimation of the stress–strength reliability in the two-parameter exponential distribution based on records
- Estimation of stress-strength reliability using record ranked set sampling scheme from the exponential distribution
- Nonparametric Upper Confidence Bounds for Pr{Y < X} and Confidence Limits for Pr{Y < X} When X and Y are Normal
- Estimation of Pr(X < Y) Using Record Values in the One and Two Parameter Exponential Distributions
- Theory of Preliminary Test and Stein‐Type Estimation With Applications
- On the comparison of the pre-test and shrinkage estimators for the univariate normal mean
This page was built for publication: Improved estimators for stress-strength reliability using record ranked set sampling scheme
