(1976). Survival Distributions: Reliability Applications in the Biomedical Sciences. Technometrics: Vol. 18, No. 4, pp. 501-501.

Survival Distributions: Reliability Applications in the Biomedical Sciences

In this paper, we estimate multicomponent stress-strength reliability by assuming Burr-XII distribution. The research methodology adopted here is to estimate the parameter using maximum likelihood estimation. Reliability is estimated using the maximum likelihood method of estimation and results are compared using the Monte Carlo simulation for small samples. Using real data sets we illustrate the procedure clearly.

Burr-XII Distribution Parametric Estimation and Estimation of Reliability of Multicomponent Stress-Strength

Survey of reliability and availability evaluation of complex networks using Monte Carlo techniques

https://isiarticles.com/bundles/Article/pre/pdf/9931.pdf

Selection between Weibull and lognormal distributions: A comparative simulation study

A multicomponent system of k components having strengths following k- independently and identically distributed random variables x 1 , x 2 , ....x k and each component experiencing a random stress Y is considered. The system is regarded as alive only if at least s out of k (s<k) strengths exceed the stress. The reliability of such a system is obtained when strength, stress variates are given by log-logistic distribution with different scale parameters. The reliability is estimated using Moment Method, ML method, Modified ML method and Best Linear Unbiased method of estimation in samples drawn from strength and stress distributions. The reliability estimators are compared asymptotically. The small sample comparison of the reliability estimates is made through Monte-Carlo simulation.

/pdf/estimation-of-reliability-in-multicomponent-stress-strength-19dxusng27.pdf

Estimation of reliability in multicomponent stress- strength model: log-logistic distribution

Estimation of reliability in multi-component stress-strength model following a Burr distribution

Reliability estimation of an s-out-of-k system with non-identical component strengths: the Weibull case

A procedure for choosing between models from two families of distributions for failure data is given. This method is based on F-statistics and can be used for a non-censored set of life testing observations. Monte Carlo samples from exponential , Wei bull , Pareto and finite range distributions are used. The performance of the proposed procedure is compared to the selection procedure S, derived by Quesenberry and Kent (1982)and to the MLR test considered by Bain and Engelhardt (l980).

Selection of probability distribution for life testing data

Adaptive estimation of parameters of some failure time distributionsis considered. A new procedure named the F-procedure has beendeveloped for selecting an appropriate model out of two possible models by Pandey et.al. (1991). Applying this F-procedure adaptive estimatorsof parameters of exponential, Wei bull, inverse Gaussian (IG) and Wald failure time distributions have been proposed in this paper. Comparison of these estimators has been undertaken with MLE's of the respective parameters and with some previous adaptiveestimators by simulation of samples using the Monte Carlo method.Adaptive estimation of parameters of some failure time distributions is considered. A new procedure named the F-procedure has been developedfor selecting an appropriate model out of two possible models by Pandey et.al. (1991). Applying this F-procedure adaptive estimators of parameters of exponential, Wei bull, inverse Gaussian (IG) and Wald failure time distributions have been proposed in this paper. Comparison of these estim...

Md. Borhan Uddin

Papers

Estimation of reliability in multi-component stress-strength model following a Burr distribution

Reliability estimation of an s-out-of-k system with non-identical component strengths: the Weibull case

Selection of probability distribution for life testing data

Effect of a new selection procedure on adaptive estimation