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Title

Modification of Sliced Inverse Regression to Censored Survival Data

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Abstract

 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.

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    APA: Copy

    Rastin, a., & Faridrohani, m.r.. (2020). Modification of Sliced Inverse Regression to Censored Survival Data. JOURNAL OF STATISTICAL SCIENCES, 13(2 ), 0-0. SID. https://sid.ir/paper/725349/en

    Vancouver: Copy

    Rastin a., Faridrohani m.r.. Modification of Sliced Inverse Regression to Censored Survival Data. JOURNAL OF STATISTICAL SCIENCES[Internet]. 2020;13(2 ):0-0. Available from: https://sid.ir/paper/725349/en

    IEEE: Copy

    a. Rastin, and m.r. Faridrohani, “Modification of Sliced Inverse Regression to Censored Survival Data,” JOURNAL OF STATISTICAL SCIENCES, vol. 13, no. 2 , pp. 0–0, 2020, [Online]. Available: https://sid.ir/paper/725349/en

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