gchol-class {bdsmatrix} | R Documentation |
The result of a generalized Cholesky decomposition A=LDL' where A is a symmetric matrix, L is lower triangular with 1s on the diagonal, and D is a diagonal matrix.
These objects are created by the gchol
function.
.Data
:A numeric vector containing the results of the decompostion
Dim
:An integer vector of length 2, the dimension of the matrix
Dimnames
:A list of length 2 containing the dimnames. These default to the dimnames of the matrix A
rank
:The rank of the matrix
signature(x = "gchol", y = "matrix")
: multiply
the cholesky decomposition by a matrix. That is, if A=LDL' is the
decomposition, then gchol(A) %*% B
will return L D^.5 B.
signature(x = "matrix", y = "gchol")
: multiply
by a matrix on the left
signature(x = "gchol")
: if a square portion from the
upper left corner is selected, then the result will be a gchol
object, otherwise an ordinary matrix is returned. The latter most
often occurs when printing part of the matrix at the command line.
signature(from = "gchol", to = "matrix")
: Use of
the as.matrix
function will return L
signature(x = "gchol")
: Use of the diag
function
will return D
signature(x = "gchol")
: returns the dimension of the
matrix
signature(x = "gchol")
: returns the dimnames
signature(object = "gchol")
: By default a triangular
matrix is printed showing D on the diagonal and L off the diagonal
signature(x= "matrix")
: create a generalized
Cholesky decompostion of the matrix
The primary advantages of the genearlized decomposition, as compared to
the standard chol function
, has to do with redundant columns
and generalized inverses (g-inverse).
The lower triangular matrix L is always of full rank. The diagonal matrix
D has a 0 element at position j if and only if the jth column of A is
linearly dependent on columns 1 to j-1 preceding it.
The g-inverse of A involves the inverse of L and a g-inverse of D.
The g-inverse of D retains the zeros and inverts non-zero elements
of D.
This is very useful inside modeling functions such as coxph
,
since the X matrix can often contain a redundant column.
Terry Therneau
showClass("gchol")