disaggregation : An R Package for Bayesian Spatial Disaggregation Modeling

Disaggregation modeling, or downscaling, has become an important discipline in epidemiology. Surveillance data, aggregated over large regions, is becoming more common, leading to an increasing demand for modeling frameworks that can deal with this data to understand spatial patterns. Disaggregation...

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Bibliographic Details
Published inJournal of statistical software Vol. 106; no. 11; pp. 1 - 19
Main Authors Nandi, Anita K., Lucas, Tim C. D., Arambepola, Rohan, Gething, Peter, Weiss, Daniel J.
Format Journal Article
LanguageEnglish
Published Foundation for Open Access Statistics 2023
Subjects
bayesian spatial modelling
disaggregation modelling
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Summary:Disaggregation modeling, or downscaling, has become an important discipline in epidemiology. Surveillance data, aggregated over large regions, is becoming more common, leading to an increasing demand for modeling frameworks that can deal with this data to understand spatial patterns. Disaggregation regression models use response data aggregated over large heterogeneous regions to make predictions at fine-scale over the region by using fine-scale covariates to inform the heterogeneity. This paper presents the R package disaggregation, which provides functionality to streamline the process of running a disaggregation model for fine-scale predictions.
ISSN:1548-7660
1548-7660
DOI:10.18637/jss.v106.i11