Repairable system model with time dependent covariate
In this paper we extend a repairable system model that incorporates both time trend and renewal-type behavior to include a time dependent covariate. We calculated the bias, standard error andrmse of the parameter estimates of this model at different sample sizes using simulated data.Following that,...
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Dixie W Publishing Corporation
2010
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my.upm.eprints.165192015-11-04T01:39:37Z http://psasir.upm.edu.my/id/eprint/16519/ Repairable system model with time dependent covariate Arasan, Jayanthi Ehsani, Samira Kiani, Kaveh In this paper we extend a repairable system model that incorporates both time trend and renewal-type behavior to include a time dependent covariate. We calculated the bias, standard error andrmse of the parameter estimates of this model at different sample sizes using simulated data.Following that, we studied several alternative computer intensive methods of constructingconfidence interval estimates for the parameters of the general model. Alternative methodsrelieve us from making assumptions and having to depend solely on the traditional methods derived from asymptotic statistical theory. In addition, the high capability of modern daycomputers makes these methods easily applicable and practical. Several parametric bootstrap methods and jackknife confidence interval procedures were compared to the Wald interval via coverage probability study. The results clearly show that the B-t and jackknife techniques work much better than other methods when sample sizes are moderate and low. The Wald intervals was found to be highly asymmetrical and only starts to work when sample sizes are rather large. Dixie W Publishing Corporation 2010 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/16519/1/Repairable%20system%20model%20with%20time%20dependent%20covariate.pdf Arasan, Jayanthi and Ehsani, Samira and Kiani, Kaveh (2010) Repairable system model with time dependent covariate. Journal of Applied Probability and Statistics, 5 (2). pp. 129-143. ISSN 1930-6792 English |
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In this paper we extend a repairable system model that incorporates both time trend and renewal-type behavior to include a time dependent covariate. We calculated the bias, standard error andrmse of the parameter estimates of this model at different sample sizes using simulated data.Following that, we studied several alternative computer intensive methods of constructingconfidence interval estimates for the parameters of the general model. Alternative methodsrelieve us from making assumptions and having to depend solely on the traditional methods derived from asymptotic statistical theory. In addition, the high capability of modern daycomputers makes these methods easily applicable and practical. Several parametric bootstrap methods and jackknife confidence interval procedures were compared to the Wald interval via coverage probability study. The results clearly show that the B-t and jackknife techniques work much better than other methods when sample sizes are moderate and low. The Wald intervals was found to be highly asymmetrical and only starts to work when sample sizes are rather large. |
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Article |
author |
Arasan, Jayanthi Ehsani, Samira Kiani, Kaveh |
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Arasan, Jayanthi Ehsani, Samira Kiani, Kaveh Repairable system model with time dependent covariate |
author_facet |
Arasan, Jayanthi Ehsani, Samira Kiani, Kaveh |
author_sort |
Arasan, Jayanthi |
title |
Repairable system model with time dependent covariate |
title_short |
Repairable system model with time dependent covariate |
title_full |
Repairable system model with time dependent covariate |
title_fullStr |
Repairable system model with time dependent covariate |
title_full_unstemmed |
Repairable system model with time dependent covariate |
title_sort |
repairable system model with time dependent covariate |
publisher |
Dixie W Publishing Corporation |
publishDate |
2010 |
url |
http://psasir.upm.edu.my/id/eprint/16519/1/Repairable%20system%20model%20with%20time%20dependent%20covariate.pdf http://psasir.upm.edu.my/id/eprint/16519/ |
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