Description: 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 POUMM 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 along a phylogenetic tree. A quick example on
using the POUMM package can be found in the README. More elaborate
examples and use-cases are provided in the vignette
Imports: ape, data.table, coda, foreach, ggplot2, GGally, gsl, Matrix

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
Imports: ape, data.table, coda, foreach, ggplot2, GGally, gsl, Matrix,

Imports: ape, data.table(>= 1.10.4), coda, foreach, ggplot2, GGally,

continuous trait evolution along a phylogenetic tree. For examples on using
Imports: ape, data.table(>= 1.10.4), coda, foreach, ggplot2, lamW,
Suggests: testthat, Rmpfr, mvtnorm, lmtest, knitr, rmarkdown, parallel,

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
Suggests: testthat, usethis, Rmpfr, mvtnorm, lmtest, knitr, rmarkdown,