Estimation of parameters from progressively censored data using EM algorithm
EM algorithm is used to determine the maximum likelihood estimates when the data are progressively Type II censored. The method is shown to be feasible and easy to implement. The asymptotic variances and covariances of the ML estimates are computed by means of the missing information principle. The...
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| Published in | Computational statistics & data analysis Vol. 39; no. 4; pp. 371 - 386 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Amsterdam
Elsevier B.V
28.06.2002
Elsevier Science Elsevier |
| Series | Computational Statistics & Data Analysis |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0167-9473 1872-7352 |
| DOI | 10.1016/S0167-9473(01)00091-3 |
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| Abstract | EM algorithm is used to determine the maximum likelihood estimates when the data are progressively Type II censored. The method is shown to be feasible and easy to implement. The asymptotic variances and covariances of the ML estimates are computed by means of the missing information principle. The methodology is illustrated with two popular models in lifetime analysis, the lognormal and Weibull lifetime distributions. |
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| AbstractList | EM algorithm is used to determine the maximum likelihood estimates when the data are progressively Type II censored. The method is shown to be feasible and easy to implement. The asymptotic variances and covariances of the ML estimates are computed by means of the missing information principle. The methodology is illustrated with two popular models in lifetime analysis, the lognormal and Weibull lifetime distributions. |
| Author | Ng, H.K.T. Chan, P.S. Balakrishnan, N. |
| Author_xml | – sequence: 1 givenname: H.K.T. surname: Ng fullname: Ng, H.K.T. organization: Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, Canada L8S 4K1 – sequence: 2 givenname: P.S. surname: Chan fullname: Chan, P.S. email: benchan@cuhk.edu.hk organization: Department of Statistics, The Chinese University of Hong Kong, Shatin, Hong Kong – sequence: 3 givenname: N. surname: Balakrishnan fullname: Balakrishnan, N. organization: Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, Canada L8S 4K1 |
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| Cites_doi | 10.2307/1267296 10.1016/S0167-7152(03)00206-2 10.1093/biomet/64.3.583 10.2307/1271448 10.2307/1267165 10.2307/1269201 10.1111/j.2517-6161.1977.tb01600.x 10.1109/TR.2002.805786 10.2307/1266337 10.1111/j.2517-6161.1982.tb01203.x |
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| Keywords | Maximum likelihood estimators Lifetime data Missing information EM algorithm Asymptotic variances Type-II progressive censoring Censored data Parameter estimation Covariance analysis Asymptotic behavior Gamma function Asymptotic variance Variance analysis Implementation Lognormal distribution Newton Raphson method Variance Statistical regression Hypothesis test Statistical test Lifetime Covariance Distribution function Asymptotic approximation Maximum likelihood Weibull distribution Weibull lifetime data |
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| SubjectTerms | Asymptotic variances EM algorithm Exact sciences and technology Lifetime data Linear inference, regression Mathematical foundations Mathematics Maximum likelihood estimators Missing information Nonparametric inference Parametric inference Probability and statistics Sciences and techniques of general use Statistics Type-II progressive censoring |
| Title | Estimation of parameters from progressively censored data using EM algorithm |
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