This article provides an overview of tensors, their properties, and their applications in
statistics. Tensors, also known as multidimensional arrays, are generalizations of matrices to …

Written by the leading expert in the field, this text reviews the major new developments in
envelope models and methods An Introduction to Envelopes provides an overview of the …

Abstract In 2011, the “ADHD-200 Global Competition” was held with the aim of identifying
biomarkers of attention-deficit/hyperactivity disorder from resting-state functional magnetic …

An optimal statistical and computational framework for generalized tensor estimation Page 1 The
Annals of Statistics 2022, Vol. 50, No. 1, 1–29 https://doi.org/10.1214/21-AOS2061 © Institute of …

Low rank tensor ring based data recovery can recover missing image entries in signal
acquisition and transformation. The recently proposed tensor ring (TR) based completion …

ABSTRACT I propose a framework for the linear prediction of a multiway array (ie, a tensor)
from another multiway array of arbitrary dimension, using the contracted tensor product. This …

The classical vector autoregressive model is a fundamental tool for multivariate time series
analysis. However, it involves too many parameters when the number of time series and lag …

Motivated by applications in neuroimaging analysis, we propose a new regression model,
Sparse TensOr REsponse regression (STORE), with a tensor response and a vector …

Multilayer tensor factorization with applications to recommender systems Page 1 The Annals of
Statistics 2018, Vol. 46, No. 6B, 3308–3333 https://doi.org/10.1214/17-AOS1659 © Institute of …

Modern scientific studies often collect datasets in the form of tensors. These datasets call for
innovative statistical analysis methods. In particular, there is a pressing need for tensor …