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Life & fun · December 23, 2023

4d-Modeller – R library to make Bayesian spatiotemporal modeling easy

Hi, I've been working with other colleagues at University of Bristol for the last year to build an R-package that makes bayesian spatio-temporal modeling easy. That is, if you have some problem like predicting sea level rise over time, disease transmissions, etc., this package may be useful for you. It centers on a collection of Shiny apps that guide you through using the various pieces of spatio-temporal modeling packages like R-INLA or inlabru. Hopefully people find this useful. I think the nice part is that we really tried to design the package so you can add it to your modeling tool kit…

4d-Modeller – R library to make Bayesian spatiotemporal modeling easy launched on December 23, 2023 with 20 votes, #853 of 3,780 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 2 years on.

Visit 4dmodeller.github.io ↗Alternativestop 23% of December 2023

In plain words

4d-Modeller is an R package developed at the University of Bristol that simplifies Bayesian spatiotemporal modeling through a collection of Shiny apps. It guides users through tools like R-INLA and inlabru for applications such as predicting sea level rise or disease transmission. The package is designed to integrate into existing modeling workflows without requiring extensive R programming knowledge.

written from the facts on this page · September 2026

From the sources

4DModeller statistical modelling package

4DModeller is a spatio-temporal modelling package that can be applied to problems at any scale from micro to processes that operate at a global scale. It includes data visualization tools, finite element mesh building tools, Bayesian hierarchical modelling based on Bayesian inference packages INLA and inlabru , and model evaluation and assessment tools. 4DModeller has been designed to make it easy to design spatially distributed, temporally dependent statistical models. Typically, 4DModeller expects tabular data sets with spatial coordinates, time indices, and the values that change or remain constant over those times. It is designed to be used in the modelling process once data has been…from 4dmodeller.github.io

In the maker’s words, at launch

Hi, I've been working with other colleagues at University of Bristol for the last year to build an R-package that makes bayesian spatio-temporal modeling easy. That is, if you have some problem like predicting sea level rise over time, disease transmissions, etc., this package may be useful for you. It centers on a…

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