4 papers · 1 filter
Addressing Phase Discrepancies in Functional Data: A Bayesian Approach for Accurate Alignment and Smoothing
Jacopo Gardella, Raffaele Argiento, Alessandro Casa +1
In many real-world applications, functional data exhibit considerable variability in both amplitude and phase. This is especially true in biomechanical data such as the knee flexio…
Confidence set for mixture order selection
Alessandro Casa, Davide Ferrari
A fundamental challenge in approximating an unknown density using finite Gaussian mixture models is selecting the number of mixture components, also known as order. Traditional app…
Model-based clustering for covariance matrices via penalized Wishart mixture models
Andrea Cappozzo, Alessandro Casa
Covariance matrices provide a valuable source of information about complex interactions and dependencies within the data. However, from a clustering perspective, this information h…
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…