| chol {base} | R Documentation |
Compute the Choleski factorization of a symmetric (Hermitian), positive definite square matrix.
chol(x, pivot = FALSE)
x |
a symmetric, positive definite matrix |
pivot |
Should pivoting be used? |
Note that only the upper triangular part of x is used, so
that R'R = x when x is symmetric.
If pivot = FALSE and x is not non-negative definite an
error occurs. If x is positive semi-definite (i.e. some zero
eigenvalues) an error may or may not occur, depending on
finite precision numerical errors.
If pivot = TRUE, then the Choleski decomposition of a positive
semi-definite x can be computed. The rank of x is
returned as attr(Q, "rank"), subject to numerical errors.
The pivot is returned as attr(Q, "pivot"). It is no longer
the case that t(Q) %*% Q equals x. However, setting
pivot <- attr(Q, "pivot") and oo <- order(pivot), it
is true that t(Q[, oo]) %*% Q[, oo] equals x,
or, alternatively, t(Q) %*% Q equals x[pivot,
pivot]. See the examples.
The upper triangular factor of the Choleski decomposition, i.e., the
matrix R such that R'R = x (see example).
If pivoting is used, then two additional attributes
"pivot" and "rank" are also returned.
The code does not check for symmetry or for non-negative
definiteness. If pivot = TRUE and x is not non-negative
definite then there will be no error message but a meaningless
result will occur. So only use pivot = TRUE when x is
non-negative definite by construction.
Dongarra, J. J., Bunch, J. R., Moler, C. B. and Stewart, G. W. (1978) LINPACK Users Guide. Philadelphia: SIAM Publications.
chol2inv for its inverse (without pivoting),
backsolve for solving linear systems with upper
triangular left sides.
qr, svd for related matrix factorizations.
( m <- matrix(c(5,1,1,3),2,2) ) ( cm <- chol(m) ) t(cm) %*% cm #-- = 'm' all(abs(m - t(cm) %*% cm) < 100* .Machine$double.eps) # TRUE x <- matrix(c(1:5, (1:5)^2), 5, 2) m <- crossprod(x) Q <- chol(m) all.equal(t(Q) %*% Q, m) # TRUE Q <- chol(m, pivot = TRUE) pivot <- attr(Q, "pivot") oo <- order(pivot) all.equal(t(Q[, oo]) %*% Q[, oo], m) # TRUE all.equal(t(Q) %*% Q, m[pivot, pivot]) # TRUE # now for something postitive semi-definite x <- cbind(x, x[, 1]+3*x[, 2]) m <- crossprod(x) qr(m)$rank # is 2, as it should be test <- try(Q <- chol(m)) (Q <- chol(m, pivot = TRUE)) # NB wrong rank here ... you have been warned! pivot <- attr(Q, "pivot") oo <- order(pivot) all.equal(t(Q[, oo]) %*% Q[, oo], m) # TRUE all.equal(t(Q) %*% Q, m[pivot, pivot]) # TRUE