Package: PCMBaseCpp 0.1.9

PCMBaseCpp: Fast Likelihood Calculation for Phylogenetic Comparative Models

Provides a C++ backend for multivariate phylogenetic comparative models implemented in the R-package 'PCMBase'. Can be used in combination with 'PCMBase' to enable fast and parallel likelihood calculation. Implements the pruning likelihood calculation algorithm described in Mitov et al. (2018) <arxiv:1809.09014>. Uses the 'SPLITT' C++ library for parallel tree traversal described in Mitov and Stadler (2018) <doi:10.1111/2041-210X.13136>.

Authors:Venelin Mitov [aut, cre, cph]

PCMBaseCpp_0.1.9.tar.gz
PCMBaseCpp_0.1.9.zip(r-4.5)PCMBaseCpp_0.1.9.zip(r-4.4)PCMBaseCpp_0.1.9.zip(r-4.3)
PCMBaseCpp_0.1.9.tgz(r-4.5-x86_64)PCMBaseCpp_0.1.9.tgz(r-4.5-arm64)PCMBaseCpp_0.1.9.tgz(r-4.4-x86_64)PCMBaseCpp_0.1.9.tgz(r-4.4-arm64)PCMBaseCpp_0.1.9.tgz(r-4.3-x86_64)PCMBaseCpp_0.1.9.tgz(r-4.3-arm64)
PCMBaseCpp_0.1.9.tar.gz(r-4.5-noble)PCMBaseCpp_0.1.9.tar.gz(r-4.4-noble)
PCMBaseCpp_0.1.9.tgz(r-4.4-emscripten)PCMBaseCpp_0.1.9.tgz(r-4.3-emscripten)
PCMBaseCpp.pdf |PCMBaseCpp.html✨
PCMBaseCpp/json (API)
NEWS

# Install 'PCMBaseCpp' in R:
install.packages('PCMBaseCpp', repos = c('https://venelin.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/venelin/pcmbasecpp/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • benchmarkData - Data for performing a benchmark
  • benchmarkResults - Results from running a performance benchmark on a personal computer including the time for parameter transformation
  • benchmarkResultsNoTransform - Results from running a performance benchmark on a personal computer excluding the time for parameter transformation

On CRAN:

Conda:

openblascpp

4.19 score 31 scripts 310 downloads 6 exports 38 dependencies

Last updated 5 years agofrom:556d2b332f. Checks:1 OK, 11 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 07 2025
R-4.5-win-x86_64NOTEMar 07 2025
R-4.5-mac-x86_64NOTEMar 07 2025
R-4.5-mac-aarch64NOTEMar 07 2025
R-4.5-linux-x86_64NOTEMar 07 2025
R-4.4-win-x86_64NOTEMar 07 2025
R-4.4-mac-x86_64NOTEMar 07 2025
R-4.4-mac-aarch64NOTEMar 07 2025
R-4.4-linux-x86_64NOTEMar 07 2025
R-4.3-win-x86_64NOTEMar 07 2025
R-4.3-mac-x86_64NOTEMar 07 2025
R-4.3-mac-aarch64NOTEMar 07 2025

Exports:BenchmarkRvsCppMiniBenchmarkRvsCppPCMBaseCppIsADevReleasePCMInfoCppPCMParamGetFullVectorPCMTreePreorderCpp

Dependencies:abindapeclicolorspacedata.tabledigestexpmfansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellmvtnormnlmePCMBasepillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangscalestibbleutf8vctrsviridisLitewithrxtable

Getting started with the PCMBaseCpp R-package

Rendered fromPCMBaseCpp.Rmdusingknitr::rmarkdownon Mar 07 2025.

Last update: 2019-11-20
Started: 2019-11-20