|
西田 喜平次 所属 京都産業大学 経営学部 職種 准教授 |
|
| 言語種別 | 英語 |
| 発行・発表の年月 | 2022/12 |
| 形態種別 | 研究論文 |
| 査読 | 査読あり |
| 標題 | Kernel Density Estimation by Stagewise Algorithm with a Simple Dictionary |
| 執筆形態 | その他 |
| 掲載誌名 | Computational Statistics |
| 掲載区分 | 国外 |
| 出版社・発行元 | Springer |
| 担当区分 | 筆頭著者,責任著者 |
| 著者・共著者 | Kiheiji NISHIDA,Kanta NAITO |
| 概要 | This study proposes multivariate kernel density estimation by stagewise minimization algorithm based on $U$-divergence and a simple dictionary. The dictionary consists of an appropriate scalar bandwidth matrix and a part of the original data. The resulting estimator brings us data-adaptive weighting parameters and bandwidth matrices, and provides a sparse representation of kernel density estimation. We develop the non-asymptotic error bound of the estimator that we obtained via the proposed stagewise minimization algorithm. It is confirmed from simulation studies that the proposed estimator performs as well as, or sometimes better than, other well-known density estimators.
(Accepted for publication on 7th Nov. 2022. Published online on 2nd Dec. 2022.) |
| DOI | 10.1007/s00180-022-01303-7 |
| PermalinkURL | http://arxiv.org/abs/2107.13430 |