Indirect multivariate response linear regression

Block Regularized Lasso for Multivariate Multi-Response Linear Regression

The multivariate multi-response (MVMR) linear regression problem is investigated, in which design matrices are Gaussian with covariance matrices Σ = ( Σ, . . . ,Σ ) for K linear regressions. The support union of K p-dimensional regression vectors (collected as columns of matrix B∗) are recovered using l1/l2-regularized Lasso. Sufficient and necessary conditions to guarantee successful recovery ...

Simultaneous Confidence Tubes in Multivariate Linear Regression

Simultaneous confidence bands have been shown in the statistical literature as powerful inferential tools in univariate linear regression. While the methodology of simultaneous confidence bands for univariate linear regression has been extensively researched and well developed, no published work seems available for multivariate linear regression. This paper fills this gap by studying one partic...

From Multivariate to Functional Linear Regression

Abstract. The aim of this contribution is to present a new, however rapidly developing domain of statistics – functional data analysis (FDA). A particular problem of extending multivariate regression to the functional setting is discussed. First of all, two real data sets and connected problems are presented. Multivariate regression is briefly recalled focusing mainly on the case of strongly co...

Bayesian regression with multivariate linear splines

Multivariate Calibration Ð Direct and Indirect Regression Methodology

This paper tries ®rst to introduce and motivate the methodology of multivariate calibration. Next a review is given, mostly avoiding technicalities, of the somewhat messy theory of the subject. Two approaches are distinguished: the estimation approach (controlled calibration) and the prediction approach (natural calibration). Among problems discussed are the choice of estimator, the choice of c...