{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T14:38:42Z","timestamp":1775572722589,"version":"3.50.1"},"reference-count":32,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2022,7,8]],"date-time":"2022-07-08T00:00:00Z","timestamp":1657238400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004377","name":"The Hong Kong Polytechnic University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004377","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Program for Innovative Research Team of Shanghai University of Finance and Economics"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,2,11]]},"abstract":"<jats:title>Summary<\/jats:title><jats:p>This article investigates the statistical problem of response-variable selection with high-dimensional response variables and a diverging number of predictor variables with respect to the sample size in the framework of multivariate linear regression. A response best-subset selection model is proposed by introducing a 0-1 selection indicator for each response variable, and then a response best-subset selector is developed by introducing a separation parameter and a novel penalized least-squares function. The proposed procedure can perform response-variable selection and regression-coefficient estimation simultaneously, and the response best-subset selector has the property of model consistency under mild conditions for both fixed and diverging numbers of predictor variables. Also, consistency and asymptotic normality of regression-coefficient estimators are established for cases with a fixed dimension, and it is found that the Bonferroni test is a special response best-subset selector. Finite-sample simulations show that the response best-subset selector has strong advantages over existing competitors in terms of the Matthews correlation coefficient, a criterion that aims to balance accuracies for both true and false response variables. An analysis of real data demonstrates the effectiveness of the response best-subset selector in an application involving the identification of dosage-sensitive genes.<\/jats:p>","DOI":"10.1093\/biomet\/asac037","type":"journal-article","created":{"date-parts":[[2022,7,8]],"date-time":"2022-07-08T13:17:46Z","timestamp":1657286266000},"page":"205-223","source":"Crossref","is-referenced-by-count":7,"title":["Response best-subset selector for multivariate regression with high-dimensional response variables"],"prefix":"10.1093","volume":"110","author":[{"given":"Jianhua","family":"Hu","sequence":"first","affiliation":[{"name":"Shanghai University of Finance and Economics School of Statistics and Management, , 777 Guoding Road, Shanghai 200433, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5218-9269","authenticated-orcid":false,"given":"Jian","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Applied Mathematics, The Hong Kong Polytechnic University , Hung Hom, Kowloon, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9774-2005","authenticated-orcid":false,"given":"Xiaoqian","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, York University , 4700 Keele Street, Toronto, Ontario M3J 1P3, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3829-1715","authenticated-orcid":false,"given":"Xu","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Statistics and Management, Shanghai University of Finance and Economics , 777 Guoding Road, Shanghai 200433, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2022,7,8]]},"reference":[{"key":"2023021111212313200_B1","volume-title":"An Introduction to Multivariate Statistical Analysis","author":"Anderson,","year":"2003","edition":"3rd ed"},{"key":"2023021111212313200_B2","doi-asserted-by":"crossref","first-page":"885","DOI":"10.1038\/ng.669","article-title":"A locus on 19p13 modifies risk of breast cancer in BRCA1 mutation carriers and is associated with hormone receptor\u2013negative breast cancer in the general population","volume":"42","author":"Antoniou,","year":"2010","journal-title":"Nature Genet."},{"key":"2023021111212313200_B3","volume-title":"The Theory of Linear Models and Multivariate Analysis","author":"Arnold,","year":"1981"},{"key":"2023021111212313200_B4","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","article-title":"Controlling the false discovery rate: A practical and powerful approach to multiple testing","volume":"57","author":"Benjamini,","year":"1995","journal-title":"J. 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