CRAN/E | POUMM

POUMM

The Phylogenetic Ornstein-Uhlenbeck Mixed Model

Installation

About

The Phylogenetic Ornstein-Uhlenbeck Mixed Model (POUMM) allows to estimate the phylogenetic heritability of continuous traits, to test hypotheses of neutral evolution versus stabilizing selection, to quantify the strength of stabilizing selection, to estimate measurement error and to make predictions about the evolution of a phenotype and phenotypic variation in a population. The package implements combined maximum likelihood and Bayesian inference of the univariate Phylogenetic Ornstein-Uhlenbeck Mixed Model, fast parallel likelihood calculation, maximum likelihood inference of the genotypic values at the tips, functions for summarizing and plotting traces and posterior samples, functions for simulation of a univariate continuous trait evolution model along a phylogenetic tree. So far, the package has been used for estimating the heritability of quantitative traits in macroevolutionary and epidemiological studies, see e.g. Bertels et al. (2017) doi:10.1093/molbev/msx246 and Mitov and Stadler (2018) doi:10.1093/molbev/msx328. The algorithm for parallel POUMM likelihood calculation has been published in Mitov and Stadler (2019) doi:10.1111/2041-210X.13136.

Citation POUMM citation info
venelin.github.io/POUMM/index.html
github.com/venelin/POUMM
Bug report File report

Key Metrics

Version 2.1.7
R ≥ 3.1.0
Published 2020-10-27 1284 days ago
Needs compilation? yes
License GPL (≥ 3.0)
CRAN checks POUMM results

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Maintainer

Maintainer

Venelin Mitov

vmitov@gmail.com

Authors

Venelin Mitov

aut / cre / cph

(<a href="https://venelin.github.io">venelin.github.io</a>)

Matt Dowle

ctb

Material

README
NEWS
Reference manual
Package source

Vignettes

Interpreting the POUMM model parameters
A User Guide to The POUMM R-package

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

POUMM archive

Depends

R ≥ 3.1.0
stats
Rcpp
methods

Imports

ape
data.table ≥ 1.13.2
coda
foreach
ggplot2
lamW
adaptMCMC
utils

Suggests

testthat
usethis
Rmpfr
mvtnorm
lmtest
knitr
rmarkdown
parallel
doParallel

LinkingTo

Rcpp