3 papers
stat.ME2021
A New Framework for Inference on Markov Population Models
Adam Walder, Ephraim M. Hanks
In this work we construct a joint Gaussian likelihood for approximate inference on Markov population models. We demonstrate that Markov population models can be approximated by a s…
stat.AP2020
Privacy for Spatial Point Process Data
Adam Walder, Ephraim M. Hanks, Aleksandra Slavković
In this work we develop methods for privatizing spatial location data, such as spatial locations of individual disease cases. We propose two novel Bayesian methods for generating s…
stat.AP2019
Bayesian Analysis of Spatial Generalized Linear Mixed Models with Laplace Random Fields
Adam Walder, Ephraim M. Hanks
Gaussian random field (GRF) models are widely used in spatial statistics to capture spatially correlated error. We investigate the results of replacing Gaussian processes with Lapl…