- tree
a phylo object with N tips.
- model
an S3 object specifying both, the model type (class, e.g. "OU") as
well as the concrete model parameter values at which the likelihood is to be
calculated (see also Details).
- W0
a numeric matrix denoting the initial k x k variance covariance matrix at the
root (default is the k x k zero matrix).
- SE
a k x N matrix specifying the standard error for each measurement in
X. Alternatively, a k x k x N cube specifying an upper triangular k x k
factor of the variance covariance matrix for the measurement error
for each tip i=1, ..., N
. When SE
is a matrix, the k x k
measurement error variance matrix for a tip i
is calculated as
VE[, , i] <- diag(SE[, i] * SE[, i], nrow = k)
. When SE
is a
cube, the way how the measurement variance matrix for a tip i
is
calculated depends on the runtime option PCMBase.Transpose.Sigma_x
as follows:
- if
getOption("PCMBase.Transpose.Sigma_x", FALSE) == FALSE
(default):
VE[, , i] <- SE[, , i] %*% t(SE[, , i])
- if
getOption("PCMBase.Transpose.Sigma_x", FALSE) == TRUE
:
VE[, , i] <- t(SE[, , i]) %*% SE[, , i]
Note that the above behavior is consistent with the treatment of the model
parameters Sigma_x
, Sigmae_x
and Sigmaj_x
, which are
also specified as upper triangular factors.
Default: matrix(0.0, PCMNumTraits(model), PCMTreeNumTips(tree))
.
metaI
a list returned from a call to PCMInfo(X, tree, model, SE)
,
containing meta-data such as N, M and k. Alternatively, this can be a
character string naming a function or a function object that returns such
a list, e.g. the functionPCMInfo
or the function PCMInfoCpp
from the PCMBaseCpp
package.
internal
a logical indicating if the per-node variance-covariances matrices for
the internal nodes should be returned (see Value). Default FALSE.
diagOnly
a logical indicating if only the variance
blocks for the nodes should be calculated. By default this is set to FALSE,
meaning that the co-variances are calculated for all couples of nodes.
verbose
logical indicating if some debug-messages should printed.