Reliability Analysis for Masked Data under Type-II Generalized Progressively Hybrid Censored Scheme

Article Preview

Abstract:

The Type-II generalized progressively hybrid censored scheme with masked data is presented. Based on masked system lifetime data, using the expectation maximization algorithm and the Quasi-Newton method, we obtain the Maximum Likelihood Estimation (MLE) of the components distribution parameters in the Weibull case. Finally, Monte Carlo simulation is presented to illustrate the effect.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1198-1201

Citation:

Online since:

November 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Kundu, D., Joarder, A., Analysis of Type-II progressively hybrid censored data. Comput. Stat. Data An. 50(2006), pp.2509-2528.

DOI: 10.1016/j.csda.2005.05.002

Google Scholar

[2] Childs, A., Chandrasekar, B., Balakrishnan, N., Exact likelihood inference for an exponential parameter under progressive hybrid censoring schemes. Statistical Models and Methods for Biomedical and Technical Systems. Birkhäuser, Boston, (2008).

DOI: 10.1007/978-0-8176-4619-6_23

Google Scholar

[3] Kundu, D., Samanta, D., Ganguly, A., Mitra, S., Bayesian analysis of different hybrid and progressive life tests. Commun. Stat. -Simul. C. 42(2013), pp.2160-2173.

DOI: 10.1080/03610918.2011.654027

Google Scholar

[4] Ng, H. K. T., Kundu D., Chan, P. S., Statistical analysis of exponential lifetimes under an adaptive Type-II progressive censoring scheme. Nav. Res. Log. 56(2009), pp.687-698.

DOI: 10.1002/nav.20371

Google Scholar

[5] Dempster, A. P., Laird, N. M., Rubin, D. B., Maximum likelihood estimation from incomplete data via the EM algorithm (with discussion). J. Royal Statistical Soc. 39(1977), pp.1-38.

DOI: 10.1111/j.2517-6161.1977.tb01600.x

Google Scholar

[6] Fan, T. H., Wang, W. L., Parameter estimation from load-sharing system data using the expectation-maximization algorithm. IEEE Trans. Reliab. 60(2011), pp.557-569.

Google Scholar