3 papers
stat.ME2024
High-dimensional Covariance Estimation by Pairwise Likelihood Truncation
Alessandro Casa, Davide Ferrari, Zhendong Huang
Pairwise likelihood is a useful approximation to the full likelihood function for covariance estimation in high-dimensional context. It simplifies high-dimensional dependencies by…
stat.ME2023
An adaptive functional regression framework for spatially heterogeneous signals in spectroscopy
Federico Ferraccioli, Alessandro Casa, Marco Stefanucci
The attention towards food products characteristics, such as nutritional properties and traceability, has risen substantially in the recent years. Consequently, we are witnessing a…
stat.CO2023
Sparse model-based clustering of three-way data via lasso-type penalties
Andrea Cappozzo, Alessandro Casa, Michael Fop
Mixtures of matrix Gaussian distributions provide a probabilistic framework for clustering continuous matrix-variate data, which are becoming increasingly prevalent in various fiel…