three.point.compute: Computations with a (generalized) three-point structured tree
In phylolm: Phylogenetic Linear Regression

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

Computes P'V^{-1}Q and the log(det V) of a (generalized) three-point structured matrix.

1 2	three.point.compute(phy, P, Q = NULL, diagWeight = NULL, check.pruningwise = TRUE, check.names = TRUE)

`phy`	a rooted phylogenetic tree of type phylo with branch lengths, to represent the 3-point structured matrix V_0. Note that the matrix of interest is V = D V_0 D.
`P,Q`	two matrices.
`diagWeight`	a vector containing the diagonal elements of the diagonal matrix D if V has a generalized 3-point structure: V = D V_0 D
`check.pruningwise`	If FALSE, the tree is assumed to be in pruningwise order.
`check.names`	if FALSE, the row names of `P`, `Q`, and the names of `diagWeight` are assumed to be the same as the labels of the tips in the tree.

`vec11`	1'V^{-1}1.
`P1`	P'V^{-1}1.
`PP`	P'V^{-1}P.
`Q1`	Q'V^{-1}1.
`QQ`	Q'V^{-1}Q.
`PQ`	P'V^{-1}Q.
`logd`	log(det V).

The matrix V is assumed to be V = D V_0 D where D is the diagonal matrix with non-zero diagonal elements in diagWeight, and where V_0 is the 3-point structured covariance matrix determined by phy and its branch lengths. Note that D do not correspond to measurement error terms.

The number of rows in P and Q and the length of diagWeight need to be the same as the number of tips in the tree. When Q = NULL, the function only returns 1'V^{-1}1, P'V^{-1}1 and P'V^{-1}P.

Lam Si Tung Ho, Robert Lachlan

Ho, L. S. T. and Ané, C. (2014). "A linear-time algorithm for Gaussian and non-Gaussian trait evolution models". Systematic Biology 63(3):397-408.

transf.branch.lengths.

tre1 = rtree(500)
tre2 = transf.branch.lengths(phy=tre1, model="OUrandomRoot",
                             parameters = list(alpha = 0.5))
Q = rTrait(n=2,tre1)
y = rTrait(n=1,tre1)
P = cbind(1,y)
three.point.compute(tre2$tree,P,Q,tre2$diagWeight)