Inferences for stress–strength reliability of Burr Type X distributions based on ranked set sampling
DOI10.1080/03610918.2020.1711949zbMath1487.62119OpenAlexW3000173489WikidataQ126344021 ScholiaQ126344021MaRDI QIDQ5866161
Fatma Gül Akgül, Birdal Şenoğlu
Publication date: 13 June 2022
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918.2020.1711949
efficiencymodified maximum likelihoodranked set samplingstress-strength reliabilityBurr type X distribution
Parametric tolerance and confidence regions (62F25) Point estimation (62F10) Bayesian inference (62F15) Sampling theory, sample surveys (62D05) Reliability and life testing (62N05)
Related Items (3)
Cites Work
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- Interval estimation of \(P(X<Y)\) in ranked set sampling
- Bayesian estimation of \(P(Y<X)\) from Burr-type \(X\) model containing spurious observations
- Resampling methods for ranked set samples
- Empirical Bayes estimation of \(P(Y<X)\) and characterizations of Burr-type \(X\) model
- Ranked set sampling. Theory and applications
- Maximum likelihood estimation of dependence parameter using ranked set sampling
- A new reliability measure in ranked set sampling
- Order statistics from the Burr type \(X\) model
- Modified maximum likelihood estimators based on ranked set samples
- Estimation of the mean of the exponential distribution using moving extremes ranked set sampling
- Estimation of the shape and scale parameters of Pareto distribution using ranked set sampling
- Point and interval estimation of \(P(X<Y)\): The normal case with common coefficient of variation
- Generalized inferences of \(R\) = \(\Pr (X>Y)\) for Pareto distribution
- Objective Bayesian analysis of the Fréchet stress-strength model
- On unbiased estimates of the population mean based on the sample stratified by means of ordering
- Inference on Pr(X Y ) Based on Record Values from the Burr Type X Distribution
- Bayesian prediction bounds for the burr type X model
- Unbiased Estimation ofP(X > Y) for Exponential Populations Using Order Statistics with Application in Ranked Set Sampling
- Ranked Set Sampling Theory with Order Statistics Background
- EstimatingP(Y < X) using Ranked Set Sampling in Case of the Exponential Distribution
- Unbiased estimation ofP(X>Y) using ranked set sample data
- Confidence Limits for Stress-Strength Models with Explanatory Variables
- Estimation of Pr{Y < X} for Exponential-Family
- Unbiased estimation of parameters by order statistics in the case of censored samples
- Reliability estimation based on ranked set sampling
- Smooth estimation of a reliability function in ranked set sampling
- On Reliability Estimation Based on Ranked Set Sampling
- Alternative Estimation Procedures for Pr(X < Y) in Categorized Data
- Inferences on stress–strength reliability based on ranked set sampling data in case of Lindley distribution
- Efficient reliability estimation in two-parameter exponential distributions
- Improved quality control charts for monitoring the process mean, using double-ranked set sampling methods
- Estimating the population proportion in pair ranked set sampling with application to air quality monitoring
- Control Charts for Monitoring Burr Type-X Percentiles
- Skip-Lot Sampling Plan of Type SkSP-2 with Two-Stage Group Acceptance Sampling Plan as Reference Plan
- The Estimation of Pr (Y < X) in the Normal Case
- Cumulative Frequency Functions
- Improving the best linear unbiased estimator for the scale parameter of symmetric distributions by using the absolute value of ranked set samples
- Inference for reliability and stress-strength for a scaled Burr type \(X\) distribution
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