4 papers
Local Level Dynamic Random Partition Models for Changepoint Detection
Alice Giampino, Bernardo Nipoti, Marina Vannucci +1
Motivated by an increasing demand for models that can effectively describe features of complex multivariate time series, e.g. from sensor data in biomechanics, motion analysis, and…
Bayesian Controlled FDR Variable Selection via Parameter-Expanded Latent Knockoffs
Lorenzo Focardi-Olmi, Anna Gottard, Michele Guindani +1
In many research fields, researchers aim to identify significant associations between a set of explanatory variables and a response while controlling the FDR. The Knockoff filter h…
Bayesian Multi-Group Functional Factor Models with Parameter-Expanded Cumulative Shrinkage Priors
Xuanye Dai, Anna Gottard, Michele Guindani +1
Functional data consist of trajectories observed over a continuous domain, such as time, space, or wavelength. Here we consider curves observed on different groups of subjects and…
Bayesian Functional Graphical Models with Change-Point Detection
Chunshan Liu, Daniel R. Kowal, James Doss-Gollin +1
Functional data analysis, which models data as realizations of random functions over a continuum, has emerged as a useful tool for time series data. Often, the goal is to infer the…