Variable selection in multi-block regression

The paper “Variable selection in multi-block regression” authored by Alessandra Biancolillo, Kristian Hovde Liland, Ingrid Måge, Tormod Næs and Rasmus Bro has been published in Chemometrics and Intelligent Laboratory Systems. Abstract The focus of the present paper is to propose and discuss different procedures for performing variable selection in a multi-block regression context. In particular, the focus is on…

Multiblock classification: SO-PLS and LDA

Combining SO-PLS and linear discriminant analysis for multi-block classification The “Combining SO-PLS and linear discriminant analysis for multi-block classification”, written by Alessandra Biancolillo, Ingrid Måge and Tormod Næs was recently published inChemometrics and Intelligent Laboratory systems. This is the first paper by Ph.D student Alessandra. Congratulations! Abstract The aim of the present work is to…

New paper accepted

Tormod Næs, Oliver Tomic, Nils Kristian Afseth, Vegard Segtnan and Ingrid Måge are authors of the newly accepted paper “Multi-block regression based on combinations of orthogonalisation, PLS-regression and canonical correlation analysis” which is to be published in the Chemometrics and Intelligent Laboratory Systems journal.

New paper accepted

The paper “Distribution based truncation for variable selection in subspace methods for multivariate regression”  has been accepted for publication in Chemometrics and Intelligent Laboratory Systems. It is authored by Kristian Hovde Liland and Harald Martens of our group together with former co-worker Martin Høy and Solve Sæbø from the Norwegian University of Life Sciences.