5 papers
K-Models: a Flexible and Interpretable Method for Ordinal Clustering with Application to Antigen-Antibody Interaction Profiles
Giulia Patanè, Alessandra Menafoglio, Alexander Krauth +4
Existing clustering methods for functional data often prioritize partitioning accuracy over interpretability, making it challenging to extract meaningful insights when the data-gen…
A Convolution Process for Sea Surface Temperature Hot-Spot Identification in the Mediterranean Sea
Leonardo Marchesin, Alessandra Menafoglio, Piercesare Secchi
Sea surface temperature (SST) is a fundamental determinant of global climate dynamics and economic activity. Reliable projections of future SST patterns depend critically on a rigo…
Robust functional PCA for relative data
Jeremy Oguamalam, Peter Filzmoser, Karel Hron +2
This paper introduces a robust approach to functional principal component analysis (FPCA) for relative data, particularly density functions. While recent papers have studied densit…
Functional-Ordinal Canonical Correlation Analysis With Application to Data from Optical Sensors
Giulia Patanè, Federica Nicolussi, Alexander Krauth +4
We address the problem of predicting a target ordinal variable based on observable features consisting of functional profiles. This problem is crucial, especially in decision-makin…
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…