deBInfer
Bayesian inference for dynamical models of biological systems in R
Science Score: 33.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
○codemeta.json file
-
○.zenodo.json file
-
✓DOI references
Found 2 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
✓Committers with academic emails
1 of 4 committers (25.0%) from academic institutions -
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (12.7%) to scientific vocabulary
Last synced: 10 months ago
·
JSON representation
Repository
Bayesian inference for dynamical models of biological systems in R
Basic Info
- Host: GitHub
- Owner: pboesu
- Language: R
- Default Branch: master
- Homepage: http://doi.org/10.1111/2041-210X.12679
- Size: 41.3 MB
Statistics
- Stars: 17
- Watchers: 5
- Forks: 4
- Open Issues: 4
- Releases: 0
Created about 10 years ago
· Last pushed over 3 years ago
Metadata Files
Readme
Contributing
Code of conduct
README.md
<!-- badges: end -->
deBInfer: Bayesian inference for dynamical models of biological systems in R
- Differential equations (DEs) are commonly used to model the temporal evolution of biological systems, but statistical methods for comparing DE models to data and for parameter inference are relatively poorly developed. This is especially problematic in the context of biological systems where observations are often noisy and only a small number of time points may be available.
- Bayesian approaches offer a coherent framework for parameter inference that can account for multiple sources of uncertainty, while making use of prior information. We present deBInfer, an R package implementing a Bayesian framework for parameter inference in DEs. This approach offers a rigorous methodology for parameter inference as well as modeling the link between unobservable model states and parameters, and observable quantities.
- deBInfer provides templates for the DE model, the observation model and data likelihood, and the model parameters and their prior distributions. A Markov chain Monte Carlo (MCMC) procedure processes these inputs to estimate the posterior distributions of the parameters and any derived quantities, including the model trajectories. Further functionality is provided to facilitate MCMC diagnostics and the visualisation of the posterior distributions of model parameters and trajectories.
- The templating approach makes deBInfer applicable to a wide range of DE models and we demonstrate its application to ordinary and delay DE models for population ecology.
For more information read our software paper or get in touch with pboesu@gmail.com
Software development is supported by NSF grant PLR-1341649.
Owner
- Name: Philipp Boersch-Supan
- Login: pboesu
- Kind: user
- Location: Cambridge, UK
- Company: British Trust for Ornithology
- Website: pboesu.github.io
- Repositories: 52
- Profile: https://github.com/pboesu
I'm an ecologist interested in the interplay between animals and the environments they inhabit. I like birds.
GitHub Events
Total
Last Year
Committers
Last synced: over 3 years ago
All Time
- Total Commits: 443
- Total Committers: 4
- Avg Commits per committer: 110.75
- Development Distribution Score (DDS): 0.111
Top Committers
| Name | Commits | |
|---|---|---|
| Philipp Boersch-Supan | p****p@b****e | 394 |
| Philipp Boersch-Supan | p****u@g****m | 22 |
| Philipp Boersch-Supan | p****n@b****g | 17 |
| Philipp Boersch-Supan | p****b@u****u | 10 |
Committer Domains (Top 20 + Academic)
Packages
- Total packages: 1
-
Total downloads:
- cran 318 last-month
- Total docker downloads: 43,390
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 4
- Total maintainers: 1
cran.r-project.org: deBInfer
Bayesian Inference for Differential Equations
- Homepage: https://github.com/pboesu/debinfer
- Documentation: http://cran.r-project.org/web/packages/deBInfer/deBInfer.pdf
- License: GPL-3
-
Latest release: 0.4.4
published over 3 years ago
Rankings
Forks count: 12.8%
Stargazers count: 14.6%
Average: 25.9%
Dependent packages count: 29.8%
Dependent repos count: 35.5%
Downloads: 36.7%
Maintainers (1)
Last synced:
11 months ago
Dependencies
DESCRIPTION
cran
- R depends
- deSolve * depends
- MASS * imports
- PBSddesolve * imports
- RColorBrewer * imports
- coda * imports
- grDevices * imports
- graphics * imports
- methods * imports
- mvtnorm * imports
- plyr * imports
- stats * imports
- truncdist * imports
- R.rsp * suggests
- beanplot * suggests
- devtools * suggests
- knitr * suggests
- rmarkdown * suggests
- testthat * suggests
.github/workflows/R-CMD-check.yaml
actions
- actions/checkout v3 composite
- r-lib/actions/check-r-package v2 composite
- r-lib/actions/setup-pandoc v2 composite
- r-lib/actions/setup-r v2-branch composite
- r-lib/actions/setup-r-dependencies v2 composite
- r-lib/actions/setup-tinytex v2 composite
.github/workflows/test-coverage.yaml
actions
- actions/cache v2 composite
- actions/checkout v2 composite
- r-lib/actions/setup-pandoc v1 composite
- r-lib/actions/setup-r v1 composite