Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1144585 | Journal of the Korean Statistical Society | 2015 | 14 Pages |
Abstract
A minimax estimator for a nonparametric regression model is proposed when real-time data are assumed and its asymptotic behavior of minimax risk in the sup-norm for the Hölder function class is studied. The optimal rate of convergence and exact minimax constant are found for the estimator.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Zhi-Ming Luo, Jeongcheol Ha, Tae Yoon Kim, Inho Park,