Package: mcbette 1.15.3

Richèl J.C. Bilderbeek

mcbette: Model Comparison Using 'babette'

'BEAST2' (<https://www.beast2.org>) is a widely used Bayesian phylogenetic tool, that uses DNA/RNA/protein data and many model priors to create a posterior of jointly estimated phylogenies and parameters. 'mcbette' allows to do a Bayesian model comparison over some site and clock models, using 'babette' (<https://github.com/ropensci/babette/>).

Authors:Richèl J.C. Bilderbeek [aut, cre], Joëlle Barido-Sottani [rev], Vikram Baliga [rev]

mcbette_1.15.3.tar.gz
mcbette_1.15.3.zip(r-4.5)mcbette_1.15.3.zip(r-4.4)mcbette_1.15.3.zip(r-4.3)
mcbette_1.15.3.tgz(r-4.4-any)mcbette_1.15.3.tgz(r-4.3-any)
mcbette_1.15.3.tar.gz(r-4.5-noble)mcbette_1.15.3.tar.gz(r-4.4-noble)
mcbette_1.15.3.tgz(r-4.4-emscripten)mcbette_1.15.3.tgz(r-4.3-emscripten)
mcbette.pdf |mcbette.html✨
mcbette/json (API)

# Install 'mcbette' in R:

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

Bug tracker:https://github.com/ropensci/mcbette/issues

Pkgdown:https://docs.ropensci.org

Uses libs:

openjdk– OpenJDK Java runtime, using Hotspot JIT

On CRAN:

openjdk

5.50 score 7 stars 18 scripts 240 downloads 15 exports 128 dependencies

Last updated 5 months agofrom:c223b0f362 (on master). Checks:OK: 3 NOTE: 4. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 27 2024
R-4.5-win	OK	Nov 27 2024
R-4.5-linux	OK	Nov 27 2024
R-4.4-win	NOTE	Nov 27 2024
R-4.4-mac	NOTE	Nov 27 2024
R-4.3-win	NOTE	Nov 27 2024
R-4.3-mac	NOTE	Nov 27 2024

Exports:calc_weights can_run_mcbette check_beast2_ns_pkg check_marg_liks check_mcbette_state est_marg_lik est_marg_liks get_mcbette_state get_test_marg_liks interpret_bayes_factor interpret_marg_lik_estimates mcbette_report mcbette_self_test plot_marg_liks set_mcbette_state

Dependencies:ade4 ape askpass babette base64enc beastier beautier bit bit64 brew brio bslib cachem callr cli clipr commonmark cpp11 crayon credentials curl desc devtools diffobj digest downlit ellipsis evaluate fansi fastmap fastmatch fontawesome fs generics gert gh gitcreds glue gmp highr hms htmltools htmlwidgets httpuv httr2 igraph ini jquerylib jsonlite knitr later lattice lifecycle magrittr MASS Matrix mauricer memoise mime miniUI nlme openssl phangorn pillar pixmap pkgbuild pkgconfig pkgdown pkgload praise prettyunits processx profvis progress promises ps purrr quadprog R6 ragg rappdirs rcmdcheck Rcpp RcppArmadillo readr remotes rJava rlang rmarkdown Rmpfr roxygen2 rprojroot rstudioapi rversions sass segmented seqinr sessioninfo shiny sourcetools sp stringi stringr sys systemfonts testit testthat textshaping tibble tidyselect tinytex tracerer txtplot tzdb urlchecker usethis utf8 vctrs vroom waldo whisker withr xfun xml2 xopen xtable yaml zip

Demo

Richèl J.C. Bilderbeek

Rendered fromdemo.Rmdusingknitr::rmarkdownon Nov 27 2024.

Last update: 2022-08-26
Started: 2020-01-14

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Calculate the weights for each marginal likelihood	calc_weights
Can 'mcbette' run?	can_run_mcbette
Checks if the BEAST2 'NS' package is installed.	check_beast2_ns_pkg
Check if the 'marg_liks' are of the same type as returned by est_marg_liks.	check_marg_liks
Check if the 'mcbette_state' is valid.	check_mcbette_state
Documentation of general function arguments. This function does nothing. It is intended to inherit function argument documentation.	default_params_doc
Estimate the marginal likelihood for an inference model.	est_marg_lik
Estimate the marginal likelihoods for one or more inference models	est_marg_liks
Get the current state of mcbette	get_mcbette_state
Get testing 'marg_liks'	get_test_marg_liks
Interpret a Bayes factor	interpret_bayes_factor
Interpret the marginal likelihood estimates	interpret_marg_lik_estimates
Determine if the 'marg_liks' is valid	is_marg_liks
Create a mcbette report, to be used when reporting bugs	mcbette_report
Performs a minimal mcbette run	mcbette_self_test
Plot the 'marg_liks'	plot_marg_liks
Set the mcbette state.	set_mcbette_state