Fused inverse regression with multi-dimensional responses

IF 0.6 Q4 STATISTICS & PROBABILITY
Youyoung Cho, Hyoseon Hana, J. Yoo
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引用次数: 0

Abstract

A regression with multi-dimensional responses is quite common nowadays in the so-called big data era. In such regression, to relieve the curse of dimension due to high-dimension of responses, the dimension reduction of predictors is essential in analysis. Su ffi cient dimension reduction provides e ff ective tools for the reduction, but there are few su ffi cient dimension reduction methodologies for multivariate regression. To fill this gap, we newly propose two fused slice-based inverse regression methods. The proposed approaches are robust to the numbers of clusters or slices and improve the estimation results over existing methods by fusing many kernel matrices. Numerical studies are presented and are compared with existing methods. Real data analysis confirms practical usefulness of the proposed methods.
多维响应的融合逆回归
在如今所谓的大数据时代,具有多维响应的回归是相当常见的。在这种回归中,为了缓解响应的高维性所带来的维数诅咒,对预测因子进行降维是分析的关键。高效降维为降维提供了有效的工具,但对于多元回归,高效降维方法却很少。为了填补这一空白,我们提出了两种基于融合切片的逆回归方法。所提出的方法对簇或切片的数量具有鲁棒性,并且通过融合多个核矩阵改善了现有方法的估计结果。给出了数值研究,并与现有方法进行了比较。实际数据分析证实了所提方法的实用性。
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来源期刊
CiteScore
0.90
自引率
0.00%
发文量
49
期刊介绍: Communications for Statistical Applications and Methods (Commun. Stat. Appl. Methods, CSAM) is an official journal of the Korean Statistical Society and Korean International Statistical Society. It is an international and Open Access journal dedicated to publishing peer-reviewed, high quality and innovative statistical research. CSAM publishes articles on applied and methodological research in the areas of statistics and probability. It features rapid publication and broad coverage of statistical applications and methods. It welcomes papers on novel applications of statistical methodology in the areas including medicine (pharmaceutical, biotechnology, medical device), business, management, economics, ecology, education, computing, engineering, operational research, biology, sociology and earth science, but papers from other areas are also considered.
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