Package: simRestore 1.1.4

simRestore: Simulate the Effect of Management Policies on Restoration Efforts

Simulation methods to study the effect of management policies on efforts to restore populations back to their original genetic composition. Allows for single-scenario simulation and for optimization of specific chosen scenarios. Further information can be found in Hernandez, Janzen and Lavretsky (2023) <doi:10.1111/1755-0998.13892>.

Authors:Thijs Janzen [aut, cre]

simRestore_1.1.4.tar.gz
simRestore_1.1.4.zip(r-4.5)simRestore_1.1.4.zip(r-4.4)simRestore_1.1.4.zip(r-4.3)
simRestore_1.1.4.tgz(r-4.5-x86_64)simRestore_1.1.4.tgz(r-4.5-arm64)simRestore_1.1.4.tgz(r-4.4-x86_64)simRestore_1.1.4.tgz(r-4.4-arm64)simRestore_1.1.4.tgz(r-4.3-x86_64)simRestore_1.1.4.tgz(r-4.3-arm64)
simRestore_1.1.4.tar.gz(r-4.5-noble)simRestore_1.1.4.tar.gz(r-4.4-noble)
simRestore_1.1.4.tgz(r-4.4-emscripten)simRestore_1.1.4.tgz(r-4.3-emscripten)
simRestore.pdf |simRestore.html✨
simRestore/json (API)

# Install 'simRestore' in R:

install.packages('simRestore', repos = c('https://thijsjanzen.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/thijsjanzen/simrestore/issues

Uses libs:

c++– GNU Standard C++ Library v3

On CRAN:

cpp

2.70 score 3 scripts 208 downloads 4 exports 37 dependencies

Last updated 1 years agofrom:0176a5d094. Checks:2 OK, 9 WARNING. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Feb 26 2025
R-4.5-win-x86_64	WARNING	Feb 26 2025
R-4.5-mac-x86_64	WARNING	Feb 26 2025
R-4.5-mac-aarch64	WARNING	Feb 26 2025
R-4.5-linux-x86_64	OK	Feb 26 2025
R-4.4-win-x86_64	WARNING	Feb 26 2025
R-4.4-mac-x86_64	WARNING	Feb 26 2025
R-4.4-mac-aarch64	WARNING	Feb 26 2025
R-4.3-win-x86_64	WARNING	Feb 26 2025
R-4.3-mac-x86_64	WARNING	Feb 26 2025
R-4.3-mac-aarch64	WARNING	Feb 26 2025

Exports:optimize_adaptive optimize_static run_shiny_app simulate_policy

Dependencies:base64enc bslib cachem cli commonmark crayon digest fansi fastmap fontawesome fs glue htmltools httpuv jquerylib jsonlite later lifecycle magrittr memoise mime pillar pkgconfig promises R6 rappdirs Rcpp rlang sass shiny sourcetools subplex tibble utf8 vctrs withr xtable

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Optimize a policy assuming a fixed total sum across all generations of individuals that can be put or pulled (e.g. a fixed effort). This fixed total sum is distributed across the generations following a beta distribution, and the parameters of this beta distribution are fitted.	optimize_adaptive
Optimize putting and/or pulling, where it is assumed that the same amount is applied per generation.	optimize_static
runs shiny app locally	run_shiny_app
Simulate the effect of a restoration policy over time.	simulate_policy