transf.branch.lengths: Creates a tree with branch lengths to represent the 3-point...
In phylolm: Phylogenetic Linear Regression

Description Usage Arguments Details Value Note Author(s) References See Also Examples

Creates a phylogenetic tree with branch lengths and a diagonal matrix to represent a (generalized) 3-point structured covariance matrix from a trait evolution model on a known tree.

transf.branch.lengths(phy, model = c("BM", "OUrandomRoot",
       "OUfixedRoot", "lambda", "kappa", "delta", "EB", "trend"),
       parameters = NULL, check.pruningwise = TRUE,
       check.ultrametric=TRUE, D=NULL, check.names = TRUE)

`phy`	a phylogenetic tree of type phylo with branch lengths.
`model`	a phylogenetic model. Default is "BM", for Brownian motion. Alternatives are "OU", "lambda", "kappa", "delta", "EB" and "trend".
`parameters`	List of parameters for the model (see Note).
`check.pruningwise`	if FALSE, the tree is assumed to be in pruningwise order.
`check.ultrametric`	if FALSE, the tree is assumed to be ultrametric and `D` needs to be provided. This is used for the OU transformations only.
`D`	vector of ajustments for the external edge lengths, to make the tree ultrametric. Used for the OU transformations only.
`check.names`	`D` needs to have names that match tip labels unless check.names=FALSE, in which case the elements in `D` are assumed to come in the same order as tip labels in the tree.

Possible phylogenetic models are the Brownian motion model (BM), the Ornstein-Uhlenbeck model (OU), Pagel's lambda model (lambda), Pagel's kappa model (kappa), Pagel's delta model (delta), the early burst model (EB), and the Brownian motion with a trend (trend). Edge lengths are unchanged under BM and the trend model. Under the kappa model, each branch length l is transformed to l^kappa. If the time from the root to a node is t in phy, it is transformed to T * (t/T)^delta under the delta model, where T is the maximum root-to-tip distance. The transformed tree has the same T. Under EB, t is transformed to (exp(rate*t)-1)/rate, which is very close to t (i.e. to the BM model) when rate is close to 0. Under the lambda model, the time t from the root to a node is transformed to lambda * t for an internal node and is unchanged for a tip. Under "OUrandomRoot", t is transformed to exp(-2 alpha (T-t)), where T is now the mean root-to-tip distance. Under "OUfixedRroot", t is transformed to exp(-2 alpha (T-t)) * (1-exp(-2 alpha t)). Under the OU models, diagWeight contains exp(alpha D_i) for tip i, where D_i is the extra length added to tip i to make the tree ultrametric.

`tree`	a rooted tree with a root edge and transformed branch lengths.
`diagWeight`	a vector containing the diagonal elements of the diagonal matrix for the generalized 3-point structure.

The default choice for the parameters are as follows: alpha=0 for the selection strength in the OU model, lambda=1, kappa=1, delta=1, rate=0 for the EB model, sigma2_error=0 for the variance of measurement errors. These default choices correspond to the BM model.

Edges in the output tree are in pruningwise order.

If model="BM" or model="trend", the output tree is the same as the input tree except that the output tree is in pruningwise order.

Lam Si Tung Ho

Ho, L. S. T. and Ane, C. A linear-time algorithm for Gaussian and non-Gaussian trait evolution models. Systematic Biology 63(3):397-408.

three.point.compute.

set.seed(123456)
tre1 = rcoal(10)
tre2 = transf.branch.lengths(phy=tre1, model="OUrandomRoot",
                             parameters = list(alpha=1))
par(mfrow = c(2,1))
plot(tre1)
plot(tre2$tree,root.edge=TRUE)