6 citations · 10 across the 3 of their papers we have counts for
4 papers
A simulation study of disaggregation regression for spatial disease mapping
Rohan Arambepola, Tim C D Lucas, Anita K Nandi +2
Disaggregation regression has become an important tool in spatial disease mapping for making fine-scale predictions of disease risk from aggregated response data. By including high…
Graphical outputs and Spatial Cross-validation for the R-INLA package using INLAutils
Tim Lucas, Andre Python, David Redding
Statistical analyses proceed by an iterative process of model fitting and checking. The R-INLA package facilitates this iteration by fitting many Bayesian models much faster than a…
disaggregation: An R Package for Bayesian Spatial Disaggregation Modelling
Anita K. Nandi, Tim C. D. Lucas, Rohan Arambepola +2
Disaggregation modelling, or downscaling, has become an important discipline in epidemiology. Surveillance data, aggregated over large regions, is becoming more common, leading to…
Variational Learning on Aggregate Outputs with Gaussian Processes
Ho Chung Leon Law, Dino Sejdinovic, Ewan Cameron +4
While a typical supervised learning framework assumes that the inputs and the outputs are measured at the same levels of granularity, many applications, including global mapping of…