4DModeller
The facts below are what the maker publishes about 4DModeller, checked and dated. Our editors have not written about it yet.
The facts
Each one read from 4DModeller's own pages, with the date it was checked.
What it does
- Bayesian analysis
- Yeschecked 23 Sep 2026
- Bayesian modelling
- Its Bayesian hierarchical modelling is based on INLA and inlabru.checked 12 Oct 2026
- Data
- It expects tabular datasets with spatial coordinates, time indices, and values that change or remain constant over time.checked 12 Oct 2026
- Data format
- The tutorial says model input should be a data frame with a response, spatial coordinates, a time index, and covariate columns when applicable.checked 11 Oct 2026
- Data import formats
- Tabular datasets with spatial coordinates, time indices, and values; specific file formats are not stated.checked 23 Sep 2026
- Data preparation
- The data preprocessing tutorial describes transforming raw data into the format needed to run a Bayesian hierarchical model with fdmr.checked 11 Oct 2026
- Deployment
- bothchecked 23 Sep 2026
- Developers
- The page names Gareth Jones as author and maintainer and lists Xueqing Yin, John Aiken, and Jonathan Bamber as authors.checked 12 Oct 2026
- Features
- The package includes data visualization, finite element mesh building, Bayesian hierarchical modelling, and model evaluation and assessment tools.checked 11 Oct 2026
- Inference integrations
- Its Bayesian hierarchical modelling is based on INLA and inlabru.checked 11 Oct 2026
- Installation
- The quickstart requires a recent R installation and gives instructions to install INLA and the fdmr package from GitHub.checked 12 Oct 2026
- Intended users
- The project is designed for users who have organized their data into tabular datasets with spatial coordinates, time indices, and values.checked 11 Oct 2026
- License
- The package is licensed under GPL (>= 3).checked 12 Oct 2026
- Mesh building
- It includes tools for building finite element meshes for model calculations.checked 12 Oct 2026
- Model evaluation
- It includes tools for evaluating and assessing model output.checked 12 Oct 2026
- Modelling
- It supports spatially distributed, temporally dependent statistical models using tabular data with spatial coordinates, time indices and measured values.checked 11 Oct 2026
- Priors
- The project describes specifying priors to help select model hyperparameters.checked 12 Oct 2026
- Purpose
- 4DModeller is a spatio-temporal modelling package for problems ranging from micro to global scales.checked 12 Oct 2026
- Scripting support
- Yeschecked 23 Sep 2026
- Support
- The project directs users to its GitHub issues page to report bugs or raise issues.checked 12 Oct 2026
- Visualization
- The package includes data visualization tools.checked 12 Oct 2026
Money
- Free plan
- Yeschecked 23 Sep 2026
Where it runs
- Linux requirement
- For Ubuntu 20.04, the installation page says some systems may need build tools and additional libraries for dependencies.checked 11 Oct 2026
- Linux support
- The installation page discusses Ubuntu 20.04 and notes that some Linux systems need additional compiler and library packages.checked 12 Oct 2026
