Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1144656 | Journal of the Korean Statistical Society | 2015 | 9 Pages |
Abstract
We propose a weighted least square method for estimation in the partial linear model with monotonicity constraints and right-censored data. This method uses the Kaplan–Meier weights to account for censoring and monotone B-splines to approximate the unknown monotone function. We show that the proposed estimator of regression coefficients is root-nn consistent and asymptotically normal under appropriate assumptions. One advantage is that our method can be easily computed using existing software. A simulation study is conducted to evaluate the finite sample performance of the proposed method.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Wei Chen, Xiaojia Li, Dehui Wang, Guohua Shi,