3 papers
stat.ME2026
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…
stat.ME2026
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…
math.ST2026
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…