Likelihood Based Estimation in the Logistic Model with Time Censored Data
Inference procedures based on the likelihood function are considered for the one logistic distribution with time censored data. The finite sample performances of the maximum likelihood estimator as well as the large sample likelihood inferential procedures based on the Wald, the Rao, and the like...
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| フォーマット: | 論文 |
| 言語: | English English |
| 出版事項: |
Universiti Putra Malaysia Press
2002
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| オンライン･アクセス: | http://psasir.upm.edu.my/id/eprint/3763/1/Likelihood_Based_Estimation_in_the_Logistic_Model.pdf http://psasir.upm.edu.my/id/eprint/3763/ |
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| 要約: | Inference procedures based on the likelihood function are considered for the
one logistic distribution with time censored data. The finite sample performances
of the maximum likelihood estimator as well as the large sample likelihood
inferential procedures based on the Wald, the Rao, and the likelihood ratio
statistics are investigated. It is found that the obtained from the asymptotic
normal distribution of the maximum likelihood estimator are found no accurate.
It is found also that interval estimation based on the Wald and Rao statistics
need much more sample size than interval estimation based on the likelihood
ratio statistics to attain reasonable accuracy. |
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