dVNodesGivenTreePOUMM: Multivariate density of observed values along a tree given an...

Description Usage Arguments Value

View source: R/likPOUMM.R


Calculates the conditional probability density of observed values at the tips and internal nodes of a tree, given that tree, the value at the root, z[N+1], where N is the number of tips in the tree, known measurement error e for each value in z, and a POUMM model of evolution. This function is mostly used to calculate the likelihood of simulated data under known model parameters.


dVNodesGivenTreePOUMM(z, tree, alpha, theta, sigma, sigmae = 0,
  e = rep(0, length(z)), log = TRUE)



A numeric vector of size length(tree$tip.label)+tree$Nnode representing the observed values at the tips, root and internal nodes.


An object of class phylo.

alpha, theta, sigma

Numeric values, parameters of the OU model.


Numeric non-negative value or vector of length(z) elements (default 0). Specifies the standard deviation of random environmental contribution (and eventually measurement error) to be added to the values. Note that if measurement standard error, se, is known and needs to be added to the environmental contribution, the right way to specify the parameter would be sqrt(sigmae^2+se^2), not sigmae+se.


Numeric vector of size length(z) representing exactly known error (sum of environmental contribution and measurement error). Defaults to a vector of zeroes.


Logical indicating whether a log-likelihood should be returned instead of a likelihood. Default is TRUE.


A numeric value, the multivariate probability density of z under the given parameters.

POUMM documentation built on Nov. 16, 2018, 1:17 a.m.