Re: [問題] 關於相關性
※ 引述《bluejaykal (黑嘛嘛)》之銘言：
: 想以模擬的方式比較 對於多重複發時間的情況之下
: margianl model 以及failty model 對於共變數的估計
: 所以以classical linear regression approach的方式
: ie. X=logY=u+beta*z+sigma
: sigma服從extreme value distribution
: 生成了一組服從獨立韋伯分佈的時間數據(X)
: 但是多重複發時間常含有相關性存在
: 想將相關性加入
: 但不知有沒有辦法能從
: 已生成的獨立韋伯分布時間
: 加入相關性
: 想請問各位大大 有沒有什麼辦法
: 感激不盡
"多重複發時間"指的是recurrent event data的setting嗎?
If yes, are you interested in modeling the recurrent events
of a subject as a renewal process or as a counting process?
The former focuses on the distribution of gap times
(the time between two consecutive events), and the latter
focuses on intensity or rate function. The two types of
approaches require different estimation methods, and usually they
are not comparable with each other.
I assume you are interested in modeling and estimation
of gap time distribution, judging from your original question.
If this is the case, you should read the simulation section
in the following papers
Wang and Chang (JASA 1999)
Huang (JRSSB 2002)
Huang and Chen (LIDA 2003)
Each of them simulated recurrent event data in a different way.
※ 編輯: bmka 來自: 71.251.54.131 (04/17 20:02)
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04/17 22:34, , 1F
04/17 22:34, 1F
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