mGS: Modified Gram-Schmidt orthogonalization of a matrix
In psvd: Eigendecomposition, Singular-Values and the Power Method
mGS R Documentation
Modified Gram-Schmidt orthogonalization of a matrix
Description
This is an internal function which uses a R code to calculate an
orthogonalization of a matrix. This function is used in the power method
allowing to compute an eigendecomposition of a symmetric square.
Usage
mGS(A)
Arguments
A
Matrix in vector form.
Value
This function returns a matrix which columns are the eigenvectors
wp
Eigevectors matrix.
Examples
A <- matrix(rnorm(6,0,1), ncol=2)
res <- mGS(A)
t(res)
psvd documentation built on Nov. 23, 2025, 5:06 p.m.
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| mGS | R Documentation |
Modified Gram-Schmidt orthogonalization of a matrix
Description
This is an internal function which uses a R code to calculate an orthogonalization of a matrix. This function is used in the power method allowing to compute an eigendecomposition of a symmetric square.
Usage
mGS(A)
Arguments
A |
Matrix in vector form. |
Value
This function returns a matrix which columns are the eigenvectors
wp |
Eigevectors matrix. |
Examples
A <- matrix(rnorm(6,0,1), ncol=2)
res <- mGS(A)
t(res)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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