research
∙
03/22/2023
GeoAdjust: Adjusting for Positional Uncertainty in Geostatistial Analysis of DHS Data
The R-package GeoAdjust https://github.com/umut-altay/GeoAdjust-package ...
share
research
∙
02/06/2023
High Resolution Global Precipitation Downscaling with Latent Gaussian Models and Nonstationary SPDE Structure
Obtaining high-resolution maps of precipitation data can provide key ins...
research
∙
01/03/2023
Spatially Varying Anisotropy for Gaussian Random Fields in Three-Dimensional Space
Isotropic covariance structures can be unreasonable for phenomena in thr...
research
∙
11/14/2022
Jittering Impacts Raster- and Distance-based Geostatistical Analyses of DHS Data
Fine-scale covariate rasters are routinely used in geostatistical models...
research
∙
07/14/2022
Spatial Aggregation with Respect to a Population Distribution
Spatial aggregation with respect to a population distribution involves e...
research
∙
02/22/2022
Accounting for Spatial Anonymization in DHS Household Surveys
The household surveys conducted by the Demographic and Health Surveys (D...
research
∙
10/18/2021
The Two Cultures for Prevalence Mapping: Small Area Estimation and Spatial Statistics
The emerging need for subnational estimation of demographic and health i...
research
∙
05/20/2021
makemyprior: Intuitive Construction of Joint Priors for Variance Parameters in R
Priors allow us to robustify inference and to incorporate expert knowled...
research
∙
07/10/2020
Space-Time Smoothing of Demographic and Health Indicators using the R Package SUMMER
The increasing availability of complex survey data, and the continued ne...
research
∙
05/24/2020
Bayesian Multiresolution Modeling Of Georeferenced Data
Current implementations of multiresolution methods are limited in terms ...
research
∙
10/15/2019
Design- and Model-Based Approaches to Small-Area Estimation in a Low and Middle Income Country Context: Comparisons and Recommendations
The need for rigorous and timely health and demographic summaries has pr...
research
∙
02/01/2019
Intuitive principle-based priors for attributing variance in additive model structures
Variance parameters in additive models are often assigned independent pr...
research
∙
02/18/2018
Spatial modelling with R-INLA: A review
Coming up with Bayesian models for spatial data is easy, but performing ...
research
∙
11/02/2017
