Hidden Markov Models of Character Evolution

Documentation for package ‘corHMM’ version 2.10.5

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ancRECON	Ancestral state reconstruction
ancRECON_slice	Ancestral state reconstruction for a particular time
ComputeCI	Compute confidence around rate estimates
compute_joint_ci	Compute joint ancestral-state reconstructions by sampling
ConvertPhangornReconstructions	Convert phangorn reconstruction to a vector
corDISC	Correlated evolution binary traits
corHMM	Hidden Rates Model
corHMMDredge	Automatic Discovery of Optimal Discrete Character Models via Simulated Annealing
corHMMDredgeBase	Fit a Single Penalized Hidden Markov Model
dent_likelihood	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_propose	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_walk	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.
dev.raydisc	Evolution of categorical traits
dropStateMatPars	Combines several rate class index matrices
equateStateMatPars	Combines several rate class index matrices
fitCorrelationTest	Test for correlation
getCVTable	Print Method for corhmm.kfold Class Objects
getFullMat	Combines several rate class index matrices
getModelTable	Summarize Model Statistics for a List of corHMM Objects
getRateCatMat	Combines several rate class index matrices
getStateMat4Dat	Produce an index matrix and legend from a dataset
get_batch_profile_lik	Perform Batch Profile Likelihood Analysis for Multiple Parameters
kFoldCrossValidation	Perform K-Fold Cross-Validation for corHMM Models
makeSimmap	Simulate a character history
node_importance_by_cluster	Identify nodes that distinguish clusters of reconstructions
phylo_aware_dist_fast	Compile a faster version of the reconstruction distance
phylo_aware_dist_local	Phylogenetically aware distance between two reconstructions
plot.dentist	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.
plotDredgeTrace	Plot the Trace of a corHMMDredge Simulated Annealing Search
plotMKmodel	Plot a Markov model
plotRECON	Plot ancestral state reconstructions
plot_batch_profile_lik	Plot Batch Profile Likelihoods
plot_clustered_phylo	Plot competing ancestral histories on a phylogeny
plot_raw_recon	Raster plot of a sample of joint reconstructions
plot_stacked_densities	Stacked log-likelihood densities by cluster
plot_transition_summary	Plot Summary Statistics of Stochastic Character Map Transitions
primates	Example datasets
primates.paint	Example datasets
print.dentist	Print dentist print summary of output from dent_walk
rayDISC	Evolution of categorical traits
rayDISC.example	Example datasets
simMarkov	Simulate a character on the tree
summarize_single_simmap	Summarize Transition Information from Stochastic Character Maps
summarize_transition_stats	Summarize Transition Information from Stochastic Character Maps
summary.dentist	Summarize dentist Display summary of output from dent_walk
tipHomology	The Probability of a Tip State Being Homologous