发表状态 | 已发表Published |
题名 | Representative points for location-biased datasets |
作者 | |
发表日期 | 2019-02-07 |
发表期刊 | Communications in Statistics: Simulation and Computation
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ISSN/eISSN | 0361-0918 |
卷号 | 48期号:2页码:458-471 |
摘要 | Representative points (RPs) are a set of points that optimally represents a distribution in terms of mean square error. When the prior data is location biased, the direct methods such as the k-means algorithm may be inefficient to obtain the RPs. In this article, a new indirect algorithm is proposed to search the RPs based on location-biased datasets. Such an algorithm does not constrain the parameter model of the true distribution. The empirical study shows that such algorithm can obtain better RPs than the k-means algorithm. |
关键词 | Good lattice point set Kernel estimator Randomized likelihood sampling Representative point |
DOI | 10.1080/03610918.2017.1385813 |
URL | 查看来源 |
收录类别 | SCIE |
语种 | 英语English |
WOS研究方向 | Mathematics |
WOS类目 | Statistics & Probability |
WOS记录号 | WOS:000462854800010 |
Scopus入藏号 | 2-s2.0-85032813337 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | https://repository.uic.edu.cn/handle/39GCC9TT/1216 |
专题 | 理工科技学院 |
通讯作者 | Zhou, Yong Dao |
作者单位 | 1.The State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, Luoyang, China 2.Institute of Statistics, Nankai University, Tianjin, China 3.College of Mathematics, Sichuan University, Chengdu, China 4.Division of Science and Technology, BNU-HKBU United International College, Zhuhai, China |
推荐引用方式 GB/T 7714 | Qi, Zong Feng,Zhou, Yong Dao,Fang, Kaitai. Representative points for location-biased datasets[J]. Communications in Statistics: Simulation and Computation, 2019, 48(2): 458-471. |
APA | Qi, Zong Feng, Zhou, Yong Dao, & Fang, Kaitai. (2019). Representative points for location-biased datasets. Communications in Statistics: Simulation and Computation, 48(2), 458-471. |
MLA | Qi, Zong Feng,et al."Representative points for location-biased datasets". Communications in Statistics: Simulation and Computation 48.2(2019): 458-471. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Qi-2019-Representati(976KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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