214 citations · 690 across the 58 of their papers we have counts for
65 papers
Multiplicative Errors-in-Variables Models for Hyperspectral Unmixing
Vivek Singh, Peter Hoff
Estimating endmember spectra and their corresponding abundances from hyperspectral images is a fundamental inverse problem in remote sensing. The standard linear mixing model relie…
Extended rank regression for all ordinal data
Peter Hoff, Supratik Basu
The accuracy of inference from a regression model depends largely on how well the model represents the relationship between the mean and variance of the outcomes. As this relations…
Testing Separability of High-Dimensional Covariance Matrices
Bongjung Sung, Peter D. Hoff
Due to their parsimony, separable covariance models have been popular in modeling matrix-variate data. However, the inference from such a model may be misleading if the population…
Information Geometry and Asymptotics for Kronecker Covariances
Andrew McCormack, Peter Hoff
We explore the information geometry and asymptotic behaviour of estimators for Kronecker-structured covariances, in both growing- and growing- scenarios, with a focus towards…
Bayesian Covariance Estimation for Multi-group Matrix-variate Data
Elizabeth Bersson, Peter D. Hoff
Multi-group covariance estimation for matrix-variate data with small within group sample sizes is a key part of many data analysis tasks in modern applications. To obtain accurate…
Core Shrinkage Covariance Estimation for Matrix-variate Data
Peter Hoff, Andrew McCormack, Anru R. Zhang
A separable covariance model for a random matrix provides a parsimonious description of the covariances among the rows and among the columns of the matrix, and permits likelihood-b…