calibrar

Automated Parameter Estimation for Complex Models

https://github.com/roliveros-ramos/calibrar

Science Score: 26.0%

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  • codemeta.json file
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  • .zenodo.json file
  • DOI references
    Found 2 DOI reference(s) in README
  • Academic publication links
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (20.5%) to scientific vocabulary

Keywords

cran modeling optimization optimization-methods r r-package
Last synced: 6 months ago · JSON representation

Repository

Automated Parameter Estimation for Complex Models

Basic Info
Statistics
  • Stars: 9
  • Watchers: 2
  • Forks: 2
  • Open Issues: 0
  • Releases: 4
Topics
cran modeling optimization optimization-methods r r-package
Created almost 12 years ago · Last pushed 11 months ago
Metadata Files
Readme Changelog

README.Rmd

---
output: github_document
---



```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README"
)
```

# calibrar 


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### Automated Parameter Estimation for Complex Models 

This R package, calibrar, has been designed for the parameter estimation (or calibration) of a wide range of ecological models, including complex and stochastic models. The package combines various optimization functionalities in a single interface, enabling the implementation of the latest advancements in complex model calibration. The package provides support for multiple phases and box constrained optimisation with the possibility of using several algorithms available in R. In particular, by using a “black-box” approach, the package allows the calibration of models implemented in any programming language. It provides a generic interface with models and allows the construction of the objective function, within R, without requiring any changes in the models' code. Parallel support for computationally intensive models is also provided, and can be used with high performance computing systems in a simple manner, including the capability to restart an unfinished optimisation for models with a long runtime.

  It implements generic functions that can be used for fitting any type of models, especially those with non-differentiable objective functions, with the same syntax as base::optim. 
  It supports multiple phases estimation (sequential parameter masking), constrained optimization (bounding box restrictions) and automatic parallel computation of numerical gradients. 
  Some common maximum likelihood estimation methods and automated construction of the objective function from simulated model outputs is provided.  
  See  for more details.

### Installation

```{r, eval = FALSE}
# The easiest way to get calibrar is to install it from CRAN:
install.packages("calibrar")

# Alternatively, install the stable development version from OSMOSE drat repository:
install.packages("calibrar", repo="https://osmose-model.github.io/drat/")

# Or the development version from GitHub:
# install.packages("remotes")
remotes::install_github("roliveros-ramos/calibrar")
```

### Usage

For a quick introduction, check the worked the examples available from the package:

```{r, eval = FALSE}
library(calibrar)
vignette("calibrar")
```

For a more detailed explanation of the package philosophy, you can read the article [calibrar: an R package for fitting complex ecological models][publication].

### Contributions

If you find any bug, have questions about the documentation or requests for enhancements, please [open an issue][issues].

Contributions are accepted as pull requests. 
Please note that the calibrar package is released with a [Contributor Code of Conduct](https://www.contributor-covenant.org/version/2/1/code_of_conduct/). By contributing to this project, you agree to abide by its terms. 


[publication]: https://doi.org/10.1111/2041-210X.14452
[issues]: https://github.com/roliveros-ramos/calibrar/issues

Owner

  • Name: Ricardo Oliveros-Ramos
  • Login: roliveros-ramos
  • Kind: user
  • Location: Montpellier, France
  • Company: IRD

Quantitative Marine Ecologist and ecosystem modeler.

GitHub Events

Total
  • Issues event: 2
  • Watch event: 2
  • Issue comment event: 1
  • Push event: 24
  • Fork event: 1
Last Year
  • Issues event: 2
  • Watch event: 2
  • Issue comment event: 1
  • Push event: 24
  • Fork event: 1

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 144
  • Total Committers: 4
  • Avg Commits per committer: 36.0
  • Development Distribution Score (DDS): 0.063
Top Committers
Name Email Commits
roliveros-ramos r****s@g****m 135
barriern n****r@i****r 4
Ricardo Oliveros-Ramos r****s@u****m 4
Giancarlo Moron g****a@g****m 1
Committer Domains (Top 20 + Academic)
ird.fr: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 6
  • Total pull requests: 1
  • Average time to close issues: over 1 year
  • Average time to close pull requests: 1 minute
  • Total issue authors: 3
  • Total pull request authors: 1
  • Average comments per issue: 1.5
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 0
  • Average time to close issues: about 1 month
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 0
  • Average comments per issue: 1.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • slehuta (3)
  • yi-xu (2)
  • bkmontgom (1)
  • raffaem (1)
Pull Request Authors
  • roliveros-ramos (1)
Top Labels
Issue Labels
bug (1) enhancement (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 268 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 2
  • Total maintainers: 1
cran.r-project.org: calibrar

Automated Parameter Estimation for Complex Models

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 268 Last month
Rankings
Stargazers count: 20.6%
Forks count: 21.0%
Dependent repos count: 23.9%
Dependent packages count: 28.7%
Average: 33.0%
Downloads: 70.9%
Maintainers (1)
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 2.15 depends
  • cmaes * imports
  • foreach * imports
  • optimr * imports
  • parallel * imports
  • stats * imports
  • utils * imports
  • deSolve * suggests
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.github/workflows/pkgdown.yaml actions
  • JamesIves/github-pages-deploy-action v4.4.1 composite
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  • r-lib/actions/setup-pandoc v2 composite
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.github/workflows/test-coverage.yaml actions
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  • r-lib/actions/setup-r v2 composite
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