Package: corHMM 2.10.4

corHMM: Hidden Markov Models of Character Evolution

Fits hidden Markov models of discrete character evolution which allow different transition rate classes on different portions of a phylogeny. Beaulieu et al (2013) <doi:10.1093/sysbio/syt034>.

Authors:Jeremy Beaulieu [aut, cre], Brian O'Meara [aut], Jeffrey Oliver [aut], James Boyko [aut], Haoyu Ji [ctb], Ben Bolker [ctb]

corHMM_2.10.4.tar.gz
corHMM_2.10.4.zip(r-4.7)corHMM_2.10.4.zip(r-4.6)corHMM_2.10.4.zip(r-4.5)
corHMM_2.10.4.tgz(r-4.6-any)corHMM_2.10.4.tgz(r-4.5-any)
corHMM_2.10.4.tar.gz(r-4.7-any)corHMM_2.10.4.tar.gz(r-4.6-any)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
corHMM/json (API)

# Install 'corHMM' in R:

install.packages('corHMM', repos = c('https://thej022214.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/thej022214/corhmm/issues

Datasets:

primates - Example datasets
primates.paint - Example datasets
rayDISC.example - Example datasets

On CRAN:

9.60 score 15 stars 2 packages 561 scripts 658 downloads 20 mentions 30 exports 58 dependencies

Last updated from:ddadab2f62. Checks:7 NOTE, 1 OK, 1 FAIL. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	NOTE	191
source / vignettes	OK	254
linux-release-x86_64	NOTE	212
macos-release-arm64	NOTE	234
macos-oldrel-arm64	NOTE	211
windows-devel	NOTE	463
windows-release	NOTE	189
windows-oldrel	NOTE	474
wasm-release	FAIL	139

Exports:ancRECON ancRECON_slice compute_joint_ci ComputeCI ConvertPhangornReconstructions corDISC corHMM corHMMDredge corHMMDredgeBase dev.raydisc dropStateMatPars equateStateMatPars fitCorrelationTest get_batch_profile_lik getCVTable getFullMat getModelTable getRateCatMat getStateMat4Dat kFoldCrossValidation makeSimmap plot_batch_profile_lik plot_transition_summary plotDredgeTrace plotMKmodel plotRECON rayDISC simMarkov summarize_single_simmap summarize_transition_stats

Dependencies:ape cli clusterGeneration coda codetools combinat corpcor cpp11 DEoptim digest doParallel expm farver fastmatch foreach generics GenSA ggplot2 glue gmp gridExtra gtable igraph isoband iterators labeling lattice lhs lifecycle magrittr maps MASS Matrix mnormt nlme nloptr nnet numDeriv optimParallel phangorn phytools pkgconfig quadprog R6 RColorBrewer Rcpp RcppEigen rlang Rmpfr RTMB S7 scales scatterplot3d TMB vctrs viridis viridisLite withr

corHMM 2.1: Generalized hidden Markov models

Rendered fromcorHMMv2.1-vignette.Rmdusingknitr::rmarkdown

Last update: 2026-03-06
Started: 2020-06-15

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Ancestral state reconstruction	ancRECON
Ancestral state reconstruction for a particular time	ancRECON_slice
Compute joint ancestral-state reconstructions by sampling	compute_joint_ci
Compute confidence around rate estimates	ComputeCI
Convert phangorn reconstruction to a vector	ConvertPhangornReconstructions
Correlated evolution binary traits	corDISC
Hidden Rates Model	corHMM
Automatic Discovery of Optimal Discrete Character Models via Simulated Annealing	corHMMDredge
Fit a Single Penalized Hidden Markov Model	corHMMDredgeBase
Dents the likelihood surface This takes any values that are better (lower) than the desired negative log likelihood and reflects them across the best_neglnL + delta line, "denting" the likelihood surface.	dent_likelihood
Propose new values This proposes new values using a normal distribution centered on the original parameter values, with desired standard deviation. If any proposed values are outside the bounds, it will propose again.	dent_propose
Sample points from along a ridge This "dents" the likelihood surface by reflecting points better than a threshold back across the threshold (think of taking a hollow plastic model of a mountain and punching the top so it's a volcano). It then uses essentially a Metropolis-Hastings walk to wander around the new rim. It adjusts the proposal width so that it samples points around the desired likelihood. This is better than using the curvature at the maximum likelihood estimate since it can actually sample points in case the assumptions of the curvature method do not hold. It is better than varying one parameter at a time while holding others constant because that could miss ridges: if I am fitting 5=x+y, and get a point estimate of (3,2), the reality is that there are an infinite range of values of x and y that will sum to 5, but if I hold x constant it looks like y is estimated very precisely. Of course, one could just fully embrace the Metropolis-Hastings lifestyle and use a full Bayesian approach.	dent_walk
Example datasets	primates primates.paint rayDISC.example
Test for correlation	fitCorrelationTest
Perform Batch Profile Likelihood Analysis for Multiple Parameters	get_batch_profile_lik
Print Method for corhmm.kfold Class Objects	getCVTable
Combines several rate class index matrices	dropStateMatPars equateStateMatPars getFullMat getRateCatMat
Summarize Model Statistics for a List of corHMM Objects	getModelTable
Produce an index matrix and legend from a dataset	getStateMat4Dat
Perform K-Fold Cross-Validation for corHMM Models	kFoldCrossValidation
Simulate a character history	makeSimmap
Plot Batch Profile Likelihoods	plot_batch_profile_lik
Plot Summary Statistics of Stochastic Character Map Transitions	plot_transition_summary
Plot the dented samples This will show the univariate plots of the parameter values versus the likelihood as well as bivariate plots of pairs of parameters to look for ridges.	plot.dentist
Plot the Trace of a corHMMDredge Simulated Annealing Search	plotDredgeTrace
Plot a Markov model	plotMKmodel
Plot ancestral state reconstructions	plotRECON
Print dentist print summary of output from dent_walk	print.dentist
Evolution of categorical traits	dev.raydisc rayDISC
Simulate a character on the tree	simMarkov
Summarize Transition Information from Stochastic Character Maps	summarize_single_simmap summarize_transition_stats
Summarize dentist Display summary of output from dent_walk	summary.dentist
The Probability of a Tip State Being Homologous	tipHomology