activity
20242026
collaborators

6 papers

stat.ME2026

Monitoring Covariance in Multichannel Profiles via Functional Graphical Models

Christian Capezza, Davide Forcina, Antonio Lepore +1

Most statistical process monitoring methods for multichannel profiles focus solely on the mean and are almost ineffective when changes involve the covariance structure. Although it…

stat.ME2025

An Adaptive Multivariate Functional Control Chart

Fabio Centofanti, Antonio Lepore, Biagio Palumbo

New data acquisition technologies allow one to gather huge amounts of data that are best represented as functional data. In this setting, profile monitoring assesses the stability…

stat.ML2024

Stream-Based Active Learning for Process Monitoring

Christian Capezza, Antonio Lepore, Kamran Paynabar

Statistical process monitoring (SPM) methods are essential tools in quality management to check the stability of industrial processes, i.e., to dynamically classify the process sta…

stat.ME2024

Functional Mixture Regression Control Chart

Christian Capezza, Fabio Centofanti, Davide Forcina +2

Industrial applications often exhibit multiple in-control patterns due to varying operating conditions, which makes a single functional linear model (FLM) inadequate to capture the…

stat.ME2024

An Adaptive Multivariate Functional EWMA Control Chart

Christian Capezza, Giovanna Capizzi, Fabio Centofanti +2

In many modern industrial scenarios, the measurements of the quality characteristics of interest are often required to be represented as functional data or profiles. This motivates…

stat.CO2024

funcharts: Control charts for multivariate functional data in R

Christian Capezza, Fabio Centofanti, Antonio Lepore +3

Modern statistical process monitoring (SPM) applications focus on profile monitoring, i.e., the monitoring of process quality characteristics that can be modeled as profiles, also…