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KCI등재 학술저널

Variable Selection in Multivariate Data

A problem of selecting a subset of the original variables based on the likelihood is considered. An appropriate perturbation scheme is attached to the variables and the likelihood displacement is computed that forms a curve in the Euclidean plane. The direction vector associated with the maximum curvature of this curve provides information about a variable that greatly change the likelihood displacement. Variables associated with large absolute components of the direction vector would be included in the model. A numerical example is given for illustration. The simulated data set shows that the variable selection procedure works well. This procedure of choosing variables would be useful for analyzing multivariate data.

1. Introduction

2. A procedure for selecting variables

3. Detailed derivations

4. A numerical example

References