Showing 1 - 10 of 180
The problem of estimation of the finite dimensional parameter in a partial linear model is considered. We derive upper and lower bounds for the second minimax order risk and show that the second order minimax estimator is a penalized maximum likelihood estimator. It is well known that the...
Persistent link: https://www.econbiz.de/10009661017
We consider a problem of estimation of parametric component in a partial linear model. Suppose that a finite set E of linear estimators is given. Our goal is to mimic the estimator in E that has the smallest risk. Using a second order expansion of the risk of linear estimators we propose a...
Persistent link: https://www.econbiz.de/10009583430
We consider a problem of estimation of parametric components in a partial linear model. Suppose that a finite set E of linear estimators is given. Our goal is to mimic the estimator in E that has the smallest risk. Using a second order expansion of the risk of linear estimators we propose a...
Persistent link: https://www.econbiz.de/10009614293
Persistent link: https://www.econbiz.de/10000728070
Persistent link: https://www.econbiz.de/10000730852
Persistent link: https://www.econbiz.de/10000735932
Persistent link: https://www.econbiz.de/10012177353
The proportional subdistribution hazards (PSH) model is popularly used to deal with competing risks data. Censored quantile regression provides an important supplement as well as variable selection methods, due to large numbers of irrelevant covariates in practice. In this paper, we study...
Persistent link: https://www.econbiz.de/10012588684
Persistent link: https://www.econbiz.de/10000707606
Persistent link: https://www.econbiz.de/10000707608