3 citations · 6 across the 3 of their papers we have counts for
3 papers
stat.CO2016★ 3 cited
Inference for log Gaussian Cox processes using an approximate marginal posterior
Shinichiro Shirota, Alan E. Gelfand
The log Gaussian Cox process is a flexible class of point pattern models for capturing spatial and spatio-temporal dependence for point patterns. Model fitting requires approximati…
stat.AP2016★ 2 cited
Space and circular time log Gaussian Cox processes with application to crime event data
Shinichiro Shirota, Alan E. Gelfand
We view the locations and times of a collection of crime events as a space-time point pattern. So, with either a nonhomogeneous Poisson process or with a more general Cox process,…
stat.ME2016★ 1 cited
Disease Mapping with Generative Models
Feifei Wang, Jian Wang, Alan E. Gelfand +1
Disease mapping focuses on learning about areal units presenting high relative risk. Disease mapping models for disease counts specify Poisson regressions in relative risks compare…