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Modification of Sliced Inverse Regression to Censored Survival Data
Azam Rastin , Mohammadreza Faridrohani
Abstract:   (278 Views)

‎The methodology of sufficient dimension reduction has offered an effective means to facilitate regression analysis of high-dimensional data‎. ‎When the response is censored‎, ‎most existing estimators cannot be applied‎, ‎or require some restrictive conditions‎. ‎In this article modification of sliced inverse‎, ‎regression-II have proposed for dimension reduction for non-linear censored regression data‎. ‎The proposed method requires no model specification‎, ‎it retains full regression information‎, ‎and it provides a usually small set of composite variables upon which subsequent model formulation and prediction can be based‎. ‎Finally‎, ‎the performance of the method is compared based on the simulation studies and some real data set include primary biliary cirrhosis data‎. ‎We also compare with the sliced inverse regression-I estimator‎.

Keywords: ‎Censored Regression‎, ‎Survival Analysis‎, ‎Sufficient Dimension Reduction‎, ‎Dimension Reduction Subspace‎, ‎Sliced Inverse Regression.
Full-Text [PDF 4182 kb]   (55 Downloads)    
Type of Study: Research | Subject: Theoritical Statistics
Received: 2018/03/4 | Accepted: 2018/11/10
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مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences
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