JOURNAL ARTICLE

Variable selection in multivariate linear regression with random predictors

Abstract

We propose a method for variable selection in multivariate regression with random predictors. This method is based on a criterion that permits to reduce the variable selection problem to a problem of estimating a suitable set. Then, an estimator for this set is proposed and the resulting method for selecting variables is shown to be consistent. A simulation study that permits to study several properties of the proposed approach and to compare it with existing methods is given.

Keywords:
Multivariate statistics Mathematics Bayesian multivariate linear regression Feature selection Selection (genetic algorithm) Estimator Statistics Linear regression Set (abstract data type) Variable (mathematics) Linear predictor function Random variable Regression Regression analysis Proper linear model Computer science Artificial intelligence

Metrics

2
Cited By
1.28
FWCI (Field Weighted Citation Impact)
22
Refs
0.71
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Statistical Methods and Models
Physical Sciences →  Mathematics →  Statistics and Probability

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