A1038
Title: High-dimensional estimation in multivariate allometric regression model
Authors: Shun Matsuura - Keio University (Japan) [presenting]
Koji Tsukuda - Kyushu University (Japan)
Abstract: Multivariate allometric regression model is a multivariate multiple regression model with multiple response variables and multiple explanatory variables, in which the directions of the differences of the mean vectors of the response variables for different values of the explanatory variables coincide with the direction of the first principal eigenvector of the covariance matrix of errors. The estimation of the common directional vector is discussed in some high-dimensional settings. Conditions for the consistency of the estimators are presented.
