Log-likelihoods for evolutionary models

Returns log-likelihood for a multivariate Ornstein-Uhlenbeck model with used defined A and R matrices..

Usage

logL.joint.multi.OUOU.user(
  init.par,
  yy,
  A.user,
  R.user,
  locations.A,
  location.diag.A,
  location.upper.tri.A,
  location.lower.tri.A,
  locations.R,
  location.diag.R,
  location.upper.tri.R
)

Arguments

init.par

initial (starting) parameters values

yy

a multivariate evoTS object

A.user

the pull matrix.

R.user

the drift matrix.

locations.A

location (row and column) of parameters (elements) in the A matrix that is estimated

location.diag.A

location (row and column) of parameters (elements) in the diagonal of the A matrix that is estimated

location.upper.tri.A

location (row and column) of parameters (elements) in the upper triangle of the A matrix that is estimated

location.lower.tri.A

location (row and column) of parameters (elements) in the lower triangle of the A matrix that is estimated

locations.R

location (row and column) of parameters (elements) in the R matrix that is estimated

location.diag.R

location (row and column) of parameters (elements) in the diagonal of the R matrix that is estimated

location.upper.tri.R

location (row and column) of parameters (elements) in the upper triangle of the R matrix that is estimated

Value

The log-likelihood of the parameter estimates, given the data.

Details

In general, users will not be access these functions directly, but instead use the optimization functions, which use these functions to find the best-supported parameter values.

Author

Kjetil Lysne Voje