3 citations · 3 across the 3 of their papers we have counts for
3 papers
stat.ME2026
Bayesian inference of sparsity in stable vector autoregressive processes
Sarah E. Heaps, Ian H. Jermyn, Yujiang Wang +1
Advances in sensing technology have made it possible to collect large volumes of high-dimensional time-series data. In fields like genetics and neuroscience, key questions concern…
stat.ME2025
Prior selection for the precision parameter of Dirichlet Process Mixtures
Carlo Vicentini, Ian Hyla Jermyn
Consider a Dirichlet process mixture model (DPM) with random precision parameter , inducing clusters over observations through its latent random partition. Our goal is…
stat.ME2022★ 3 cited
Structured prior distributions for the covariance matrix in latent factor models
Sarah Elizabeth Heaps, Ian Hyla Jermyn
Factor models are widely used for dimension reduction in the analysis of multivariate data. This is achieved through decomposition of a p x p covariance matrix into the sum of two…