predictHiddenStateWithPE: Predict hidden state under the PE model

In wu-lab-uva/RasperGade: Reconstructing Ancestral State under Pulsed Evolution in R by Gaussian Decomposition

Predict hidden state under the PE model

Description

Predict hidden state under the PE model given a phylogeny, some known states, and the PE model

Usage

predictHiddenStateWithPE(
  FMR,
  query.keys,
  laplace = FALSE,
  numApprox = 1,
  margin = 1e-06,
  asymptotic = 5,
  numCores = 1
)

Arguments

FMR	the returned data structure from function fullMarginalReconstructionWithPE
query.keys	the tracking key of query tips
laplace	logical, if true, Laplace distribution is used for time-independent variation
numApprox	the number of normal distributions to approximate the Laplace distribution
margin	the total probability mass that the number of jumps omitted in a compound Poisson process
asymptotic	the threshold of expected number of jumps on a branch beyond which normal distribution is assumed
numCores	the number of cores to run in parallel

Value

a list of two elements:

$summary is a data frame listing the means and variances of the hidden states

$error is a list of error distributions#' @details to be added

wu-lab-uva/RasperGade documentation built on June 24, 2022, 2:47 p.m.