On multivariate linear regression shrinkage and reduced-rank procedures

被引：4
|
作者：
Reinsel, GC [1 ]
机构：
[1] Univ Wisconsin, Dept Stat, Madison, WI 53706 USA
来源：
JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 1999年 / 81卷 / 02期
关键词：
canonical correlation analysis; multivariate regression; prediction mean square error; reduced rank; shrinkage;
D O I：
10.1016/S0378-3758(99)00016-6
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
An alternate derivation of the canonical analysis shrinkage prediction procedure of Breiman and Friedman (1997. J. Roy. Statist. Sec. B 59, 3-54) is presented for the multivariate linear model. It is based on consideration of prediction mean square error matrix, and bias of the squared sample canonical correlations. A modified procedure involving partial canonical correlation analysis is also introduced and discussed. (C) 1999 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：311 / 321
页数：11
相关论文
共 50 条
  • [1] PROCEDURES FOR REDUCED-RANK REGRESSION
    DAVIES, PT
    TSO, MKS
    [J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 1982, 31 (03) : 244 - 255
  • [2] Reduced-rank linear regression
    Stoica, P
    Viberg, M
    [J]. 8TH IEEE SIGNAL PROCESSING WORKSHOP ON STATISTICAL SIGNAL AND ARRAY PROCESSING, PROCEEDINGS, 1996, : 542 - 545
  • [3] Partially reduced-rank multivariate regression models
    Reinsel, Gregory C.
    Velu, Raja P.
    [J]. STATISTICA SINICA, 2006, 16 (03) : 899 - 917
  • [4] Efficient estimation of reduced-rank partial envelope model in multivariate linear regression
    Zhang, Jing
    Huang, Zhensheng
    Xiong, Yan
    [J]. RANDOM MATRICES-THEORY AND APPLICATIONS, 2021, 10 (02)
  • [5] Envelope-based sparse reduced-rank regression for multivariate linear model
    Guo, Wenxing
    Balakrishnan, Narayanaswamy
    He, Mu
    [J]. JOURNAL OF MULTIVARIATE ANALYSIS, 2023, 195
  • [6] On the degrees of freedom of reduced-rank estimators in multivariate regression
    Mukherjee, A.
    Chen, K.
    Wang, N.
    Zhu, J.
    [J]. BIOMETRIKA, 2015, 102 (02) : 457 - 477
  • [7] Multivariate prediction using softly shrunk reduced-rank regression
    Aldrin, M
    [J]. AMERICAN STATISTICIAN, 2000, 54 (01): : 29 - 34
  • [8] A fully Bayesian approach to sparse reduced-rank multivariate regression
    Yang, Dunfu
    Goh, Gyuhyeong
    Wang, Haiyan
    [J]. STATISTICAL MODELLING, 2022, 22 (03) : 199 - 220
  • [9] MODEL FREE MULTIVARIATE REDUCED-RANK REGRESSION WITH CATEGORICAL PREDICTORS
    Setodji, Claude Messan
    Li, Lexin
    [J]. STATISTICA SINICA, 2009, 19 (03) : 1119 - 1136
  • [10] Multivariate Functional Regression Via Nested Reduced-Rank Regularization
    Liu, Xiaokang
    Ma, Shujie
    Chen, Kun
    [J]. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 2022, 31 (01) : 231 - 240
12345