Partial Least Squares for Heterogeneous Data

DOI10.1007/978-3-319-40643-5_1zbMath1366.62131OpenAlexW2531046643MaRDI QIDQ5278351

Peter Bühlmann

Publication date: 19 July 2017

Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-40643-5_1

zbMATH Keywords

minimaxmaximinbig dataheterogeneous datapartial least square regression (PLSR)

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Minimax procedures in statistical decision theory (62C20)

Related Items (1)

High-Dimensional Factor Regression for Heterogeneous Subpopulations

Uses Software

• R
• S-PLUS
• ElemStatLearn
• MEMSS

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Bagging predictors
• Statistics for high-dimensional data. Methods, theory and applications.
• Analyzing bagging
• Handbook of partial least squares. Concepts, methods and applications.
• Maximin effects in inhomogeneous large-scale data
• Mixed-Effects Models in S and S-PLUS
• A Statistical View of Some Chemometrics Regression Tools
• Properties of Bagged Nearest Neighbour Classifiers
• Ridge Regression: Biased Estimation for Nonorthogonal Problems

This page was built for publication: Partial Least Squares for Heterogeneous Data