gramschmidt: Gram-Schmidt

In pracma: Practical Numerical Math Functions

Gram-Schmidt

Description

Modified Gram-Schmidt Process

Usage

  gramSchmidt(A, tol = .Machine$double.eps^0.5)

Arguments

A	numeric matrix with nrow(A)>=ncol(A).
tol	numerical tolerance for being equal to zero.

Details

The modified Gram-Schmidt process uses the classical orthogonalization process to generate step by step an orthonoral basis of a vector space. The modified Gram-Schmidt iteration uses orthogonal projectors in order ro make the process numerically more stable.

Value

List with two matrices Q and R, Q orthonormal and R upper triangular, such that A=Q%*%R.

References

Trefethen, L. N., and D. Bau III. (1997). Numerical Linear Algebra. SIAM, Society for Industrial and Applied Mathematics, Philadelphia.

See Also

householder, givens

Examples

##  QR decomposition
A <- matrix(c(0,-4,2, 6,-3,-2, 8,1,-1), 3, 3, byrow=TRUE)
gs <- gramSchmidt(A)
(Q <- gs$Q); (R <- gs$R)
Q %*% R  # = A

pracma documentation built on March 19, 2024, 3:05 a.m.