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nimblewomble: An R package for Bayesian Wombling with nimble
Journal article   Open access   Peer reviewed

nimblewomble: An R package for Bayesian Wombling with nimble

Aritra Halder and Sudipto Banerjee
The R journal, v 18(2), pp 71-84
16 Jul 2026
url
https://doi.org/10.32614/RJ-2026-026View
Published, Version of Record (VoR) Open

Abstract

This exposition presents nimblewomble, a software package to perform wombling, or boundary analysis, using the nimble Bayesian hierarchical modeling language in the R statistical computing environment. Wombling is used widely to track regions of rapid change within the spatial reference domain. Specific functions in the package implement Gaussian process models for point-referenced spatial data followed by predictive inference on rates of change over curves using line integrals. We demonstrate model-based Bayesian inference using posterior distributions featuring simple analytic forms while offering uncertainty quantification over curves.

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