Name
Abstract | ||
|---|---|---|
The present study proposes the classical and Bayesian treatment to the estimation problem of parameters of a k-components load-sharing parallel system in which some of the components follow a constant failure-rate and the remaining follow a linearly increasing failure-rate. In the classical setup, the maximum likelihood estimates of the load-share parameters with their variances are obtained. (1-@c)100% individual, simultaneous, Bonferroni simultaneous and two bootstrap confidence intervals for the parameters have been constructed. Further, on recognizing the fact that life testing experiments are very time consuming, the parameters involved in the failure time distributions of the system are expected to follow some random variations. Therefore, Bayes estimates along with their posterior variances of the parameters are obtained by assuming gamma and Jeffrey's invariant priors. Markov Chain Monte Carlo techniques such as a Gibbs sampler have also been used to obtain the Bayes estimates and highest posterior density credible intervals when all the parameters follow gamma priors. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.csda.2008.05.026 | Computational Statistics & Data Analysis |
Keywords | Field | DocType |
classical setup,bayesian treatment,failure time distribution,constant failure-rate,posterior variance,parallel system,highest posterior density,bayesian estimation,gamma prior,bayes estimate,time consuming,maximum likelihood estimate,bayes estimator,markov chain monte carlo,gibbs sampler,confidence interval,credible interval,failure rate,parallel systems | Econometrics,Markov chain Monte Carlo,Markov chain,Posterior probability,Estimation theory,Prior probability,Statistics,Bayes estimator,Gibbs sampling,Mathematics,Bayes' theorem | Journal |
Volume | Issue | ISSN |
52 | 12 | Computational Statistics and Data Analysis |
Citations | PageRank | References |
12 | 1.17 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bhupendra Singh | 1 | 35 | 5.44 |
| Ajay K. Sharma | 2 | 139 | 25.90 |
| Anuj Kumar | 3 | 12 | 1.85 |