71 citations · 152 across the 35 of their papers we have counts for
39 papers
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…
Small Area Estimation with Random Forests and the LASSO
Victoire Michal, Jon Wakefield, Alexandra M. Schmidt +3
We consider random forests and LASSO methods for model-based small area estimation when the number of areas with sampled data is a small fraction of the total areas for which estim…
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…
Modeling Urban/Rural Fractions in Low- and Middle-Income Countries
Yunhan Wu, Jon Wakefield
In low- and middle-income countries, household surveys are the most reliable data source to examine health and demographic indicators at the subnational level, an exercise in small…
Incorporating testing volume into estimation of effective reproduction number dynamics
Isaac H. Goldstein, Jon Wakefield, Volodymyr M. Minin
Branching process inspired models are widely used to estimate the effective reproduction number -- a useful summary statistic describing an infectious disease outbreak -- using cou…
Spatial Aggregation with Respect to a Population Distribution
John Paige, Geir-Arne Fuglstad, Andrea Riebler +1
Spatial aggregation with respect to a population distribution involves estimating aggregate quantities for a population based on an observation of individuals in a subpopulation. I…