Maximum Likelihood Estimator of Current Status Data under Bernstein Proportional Odds Cure Model
碩士 === 中原大學 === 應用數學研究所 === 102 === In this paper, we use Maximum Likelihood Estimator of Current Status Data under Bernstein Proportion Odds Cure Model to carry out research under Ching-Hung Liu’s Thesis (2012) , using the Weibull distribution survival distribution of time to do, is to use the esti...
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ndltd-TW-102CYCU55070122019-05-15T21:14:00Z http://ndltd.ncl.edu.tw/handle/sdg937 Maximum Likelihood Estimator of Current Status Data under Bernstein Proportional Odds Cure Model 現狀數據在伯氏比率勝算比治癒率模型下之最大概似估計 Wen-Chieh Tai 戴文傑 碩士 中原大學 應用數學研究所 102 In this paper, we use Maximum Likelihood Estimator of Current Status Data under Bernstein Proportion Odds Cure Model to carry out research under Ching-Hung Liu’s Thesis (2012) , using the Weibull distribution survival distribution of time to do, is to use the estimated parameters maximum likelihood estimator, we use Bernstein polynomials to replace the Weibull distribution, the estimated parameters are also using maximum likelihood estimator. In making the maximum likelihood estimate, because many parameters and we are not fixed, so we will use the Monte Carlo Markov chain (M.C.M.C.) to calculate the maximum likelihood estimator, and the potential to make a distribution function graphic factors, write another basis for the comparison of algorithms and general graphics algorithms that map looks like if found, then use a graphical algorithm which estimates the optimum. Yuh-Jenn Wu 吳裕振 2014 學位論文 ; thesis 24 zh-TW |
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碩士 === 中原大學 === 應用數學研究所 === 102 === In this paper, we use Maximum Likelihood Estimator of Current Status Data under Bernstein Proportion Odds Cure Model to carry out research
under Ching-Hung Liu’s Thesis (2012) , using the Weibull distribution survival distribution of time to do, is to use the estimated parameters
maximum likelihood estimator, we use Bernstein polynomials to replace the Weibull distribution, the estimated parameters are also using maximum
likelihood estimator.
In making the maximum likelihood estimate, because many parameters and we are not fixed, so we will use the Monte Carlo Markov chain (M.C.M.C.) to calculate the maximum likelihood estimator, and the potential to make a distribution function graphic factors, write another basis for the comparison of algorithms and general graphics algorithms that
map looks like if found, then use a graphical algorithm which estimates the optimum.
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author2 |
Yuh-Jenn Wu |
author_facet |
Yuh-Jenn Wu Wen-Chieh Tai 戴文傑 |
author |
Wen-Chieh Tai 戴文傑 |
spellingShingle |
Wen-Chieh Tai 戴文傑 Maximum Likelihood Estimator of Current Status Data under Bernstein Proportional Odds Cure Model |
author_sort |
Wen-Chieh Tai |
title |
Maximum Likelihood Estimator of Current Status Data under Bernstein Proportional Odds Cure Model |
title_short |
Maximum Likelihood Estimator of Current Status Data under Bernstein Proportional Odds Cure Model |
title_full |
Maximum Likelihood Estimator of Current Status Data under Bernstein Proportional Odds Cure Model |
title_fullStr |
Maximum Likelihood Estimator of Current Status Data under Bernstein Proportional Odds Cure Model |
title_full_unstemmed |
Maximum Likelihood Estimator of Current Status Data under Bernstein Proportional Odds Cure Model |
title_sort |
maximum likelihood estimator of current status data under bernstein proportional odds cure model |
publishDate |
2014 |
url |
http://ndltd.ncl.edu.tw/handle/sdg937 |
work_keys_str_mv |
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1719111416830492672 |