Nonparametric Tests Under Mixture Models
碩士 === 東海大學 === 統計學系 === 86 === Under mixture models, the distribution function for lifetime Xi of an individual i drawn at random is F(x)=(1-PI)Fd(x) for x in [0, tau_f], where 0<=PI< 1 denotes the proportion of `immune' or `cured' individuals,Fd(x) denotes the distribut...
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ndltd-TW-086THU005060012015-10-13T17:34:44Z http://ndltd.ncl.edu.tw/handle/72930083798275936280 Nonparametric Tests Under Mixture Models 混合模式下之無母數檢定 Chen,Chien-Chang 陳建彰 碩士 東海大學 統計學系 86 Under mixture models, the distribution function for lifetime Xi of an individual i drawn at random is F(x)=(1-PI)Fd(x) for x in [0, tau_f], where 0<=PI< 1 denotes the proportion of `immune' or `cured' individuals,Fd(x) denotes the distribution function of `susceptible' individuals with the right extreme tau_f. Assuming an independent censoring model, observations are of the formTi=min{Xi,Ci} (i=1,...,n), where Ci's are censoring times with right extreme tau_g and independent of Xi's.Assuming PI>0,they propose a nonparametric statistic to test H0:tau_f>=tau_g versus Ha:tau_f<tau_g.In this article, it is shown that under Ha the power of the test converges to 1. However, our investigation shows that the test is not able to control Type I error for testing the hypothesis of H0.It is pointed out that assuming tau_f<tau_g,the test is useful for testing the hypothesis of H0^:PI=0 versus Ha^:PI>0. Shen, Pao-Sheng 沈葆聖 1998 學位論文 ; thesis 12 en_US |
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碩士 === 東海大學 === 統計學系 === 86 === Under mixture models, the distribution function for lifetime Xi of an individual i drawn at random is F(x)=(1-PI)Fd(x) for x in [0, tau_f], where 0<=PI< 1 denotes the proportion of `immune' or `cured' individuals,Fd(x) denotes the distribution function of `susceptible' individuals with the right extreme tau_f. Assuming an independent censoring model, observations are of the formTi=min{Xi,Ci} (i=1,...,n), where Ci's are censoring times with right extreme tau_g and independent of Xi's.Assuming PI>0,they propose a nonparametric statistic to test H0:tau_f>=tau_g versus Ha:tau_f<tau_g.In this article, it is shown that under Ha the power of the test converges to 1. However, our investigation shows that the test is not able to control Type I error for testing the hypothesis of H0.It is pointed out that assuming tau_f<tau_g,the test is useful for testing the hypothesis of H0^:PI=0 versus Ha^:PI>0.
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author2 |
Shen, Pao-Sheng |
author_facet |
Shen, Pao-Sheng Chen,Chien-Chang 陳建彰 |
author |
Chen,Chien-Chang 陳建彰 |
spellingShingle |
Chen,Chien-Chang 陳建彰 Nonparametric Tests Under Mixture Models |
author_sort |
Chen,Chien-Chang |
title |
Nonparametric Tests Under Mixture Models |
title_short |
Nonparametric Tests Under Mixture Models |
title_full |
Nonparametric Tests Under Mixture Models |
title_fullStr |
Nonparametric Tests Under Mixture Models |
title_full_unstemmed |
Nonparametric Tests Under Mixture Models |
title_sort |
nonparametric tests under mixture models |
publishDate |
1998 |
url |
http://ndltd.ncl.edu.tw/handle/72930083798275936280 |
work_keys_str_mv |
AT chenchienchang nonparametrictestsundermixturemodels AT chénjiànzhāng nonparametrictestsundermixturemodels AT chenchienchang hùnhémóshìxiàzhīwúmǔshùjiǎndìng AT chénjiànzhāng hùnhémóshìxiàzhīwúmǔshùjiǎndìng |
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1717780999683702784 |