tdsa

https://github.com/weehaong/tdsa

Science Score: 39.0%

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CITATION.cff file
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codemeta.json file
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DOI references
Found 9 DOI reference(s) in README
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Low similarity (12.2%) to scientific vocabulary

Last synced: 10 months ago · JSON representation

Repository

Basic Info

Host: GitHub
Owner: weehaong
License: gpl-3.0
Language: HTML
Default Branch: main
Size: 1.21 MB

Statistics

Stars: 0
Watchers: 1
Forks: 0
Open Issues: 0
Releases: 2

Created about 3 years ago · Last pushed about 1 year ago

Metadata Files

Readme Changelog License

tdsa: An R package to perform time-dependent sensitivity analysis

Wee Hao Ng

May 15, 2025

Introduction

This package automates the steps required to perform time-dependent sensitivity analysis (TDSA), for both continuous- and discrete-time models. Refer to the bibliography for the theory behind TDSA, and the vignette for a simple demonstration of how to use the package.

Installation

The package requires R version (>= 3.5.0).

CRAN

To install the ranger R package from CRAN, use the R command

    install.packages("tdsa")

This should also install any dependencies that are missing.

Github

To install from GitHub, the easiest way is to use devtools, using the R command

    devtools::install_github("weehaong/tdsa")

To install from GitHub without using devtools: 1. Install the dependencies deSolve, mathjaxr and numDeriv.

Download and unpack the repository from GitHub.
Build the package using the OS terminal command
```
R CMD build path_to_folder
```
The argument path_to_folder in the command should point to the folder containing the unpacked repository. This will create a tarball (.tar.gz file), e.g. tdsa_1.0-1.tar.gz. Note that for Windows users, RTools will need to be installed, and both R and RTools added to the system or user path.
Install the tarball. This can be done using the R command
```
install.packages(path_to_tarball, repos=NULL, type="source")
```
where path_to_tarball should point to the tarball file created in the previous step.

Bibliography

Ng, W. H., Myers, C. R., McArt, S., & Ellner, S. P. (2023). A time for every purpose: using time-dependent sensitivity analysis to help understand and manage dynamic ecological systems. American Naturalist, 202, 630–654. doi: 10.1086/726143. eprint doi: 10.1101/2023.04.13.536769.

Ng, W. H., Myers, C. R., McArt, S., & Ellner, S. P. (2023). tdsa: An R package to perform time-dependent sensitivity analysis. Methods in Ecology and Evolution, 14, 2758–2765. doi: 10.1111/2041-210X.14216.

Owner

Login: weehaong
Kind: user

Repositories: 1
Profile: https://github.com/weehaong

GitHub Events

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Last synced: 10 months ago

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Packages

Total packages: 1
Total downloads:
- cran 464 last-month

Total dependent packages: 0
Total dependent repositories: 0
Total versions: 4
Total maintainers: 1

cran.r-project.org: tdsa

Time-Dependent Sensitivity Analysis

Homepage: https://github.com/weehaong/tdsa
Documentation: http://cran.r-project.org/web/packages/tdsa/tdsa.pdf
License: GPL-3
Latest release: 1.1-1
published about 1 year ago

Versions: 4
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 464 Last month

Rankings

Dependent packages count: 29.6%

Dependent repos count: 35.3%

Average: 51.5%

Downloads: 89.7%

Maintainers (1)

wn68@cornell.edu