4 papers
Semi-Parametric Inference for Doubly Stochastic Spatial Point Processes: An Approximate Penalized Poisson Likelihood Approach
Si Cheng, Jon Wakefield, Ali Shojaie
Doubly-stochastic point processes model the occurrence of events over a spatial domain as an inhomogeneous Poisson process conditioned on the realization of a random intensity func…
The Two Cultures of Prevalence Mapping: Small Area Estimation and Model-Based Geostatistics
Jon Wakefield, Peter A. Gao, Geir-Arne Fuglstad +1
In low- and middle-income countries (LMICs), accurate estimates of subnational health and demographic indicators are critical for guiding policy and identifying disparities. Many i…
BARTSIMP: flexible spatial covariate modeling and prediction using Bayesian additive regression trees
Alex Ziyu Jiang, Jon Wakefield
Prediction is a classic challenge in spatial statistics and the inclusion of spatial covariates can greatly improve predictive performance when incorporated into a model with laten…
Space-Time Smoothing of Survey Outcomes using the R Package SUMMER
Zehang Richard Li, Bryan D Martin, Tracy Qi Dong +5
The increasing availability of complex survey data, and the continued need for estimates of demographic and health indicators at a fine spatial and temporal scale, which leads to i…