Covariate Information Matrix for Sufficient Dimension Reduction-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Covariate Information Matrix for Sufficient Dimension Reduction

Published:2019-02-27 Issue:528 Volume:114 Page:1752-1764
ISSN:0162-1459
Container-title:Journal of the American Statistical Association
language:en
Short-container-title:Journal of the American Statistical Association

Author:

Yao Weixin¹,Nandy Debmalya²,Lindsay Bruce G.²,Chiaromonte Francesca²³

Affiliation:

1. Department of Statistics, University of California, Riverside, Riverside, CA;

2. Department of Statistics, Penn State University, University Park, PA;

3. Institute of Economics and EMbeDS, Sant’Anna School of Advanced Studies, Piazza Martiri della Libertà, Pisa, Italy

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2018.1515080

Reference61 articles.

1. The vector representation of a sample

2. Adaptive Smoothing and Density-Based Tests of Multivariate Normality

3. Estimating Optimal Transformations for Multiple Regression and Correlation

4. Dimension estimation in sufficient dimension reduction: A unifying approach

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A structured covariance ensemble for sufficient dimension reduction;Advances in Data Analysis and Classification;2022-10-19

2. On reconsidering entropies and divergences and their cumulative counterparts: Csiszár's, DPD's and Fisher's type cumulative and survival measures;Probability in the Engineering and Informational Sciences;2022-02-21

3. Sufficient Dimension Reduction: An Information-Theoretic Viewpoint;Entropy;2022-01-22

4. Covariate Information Number for Feature Screening in Ultrahigh-Dimensional Supervised Problems;Journal of the American Statistical Association;2021-02-10

5. Semiparametric mixtures of regressions with single-index for model based clustering;Advances in Data Analysis and Classification;2020-04-23

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3