matop: matop

Description

Compute the SVD or QR decomposition of the matrix X.

Usage

matop(y = NULL, X, method = c("svd", "qr"), bigmat = TRUE)

Value

If the method used is svd then the list containing the following components:

y: The data vector (numeric, n) NAs allowed.
X: Design Matrix of dimension n x p.
D: A vector containing the singular values of X, of lenght min(n,p).
L: A matrix whose columns contain the left singular vectors of X,
R: A matrix whose columns contain the right singular vectors of X.
ev: A vector containing the square of D.
Ly: The cross-product between the matrix L and vector y.
n: Number of rows of X.
p: Number of columns of X.

If the method used is qr then the list containing the following components:

y: The data vector (numeric, n) NAs allowed.
X: Design Matrix of dimension n x p.
R: An upper triangular matrix of dimension n x p.
n: Number of rows of X.
p: Number of columns of X.

Arguments

y: The data vector (numeric, n) NAs allowed. The default value is NULL, It is possible to compute the SVD or QR decomposition without y.
X: Design Matrix of dimension n x p.
method: Options for the posterior computation. Two methods, "qr" and "svd" decomposition. The default value for the method is SVD descomposition.
bigmat: Use of the bigstatsr package. The default value for bigmat is TRUE.

Author

Sergio Perez-Elizalde, Blanca E. Monroy-Castillo, Paulino Perez-Rodriguez.

Details

Use the bigstartsr package when p >> n. Auxiliary in the HDBRR function.

Examples

Run this code

n <- 30
p <- 100
X <- matrix(rnorm(n*(p-1),1,1/p),nrow = n,ncol = p-1)
Beta <- sample(1:p,p-1,rep = FALSE)
Beta <- c(1,Beta)
y <- cbind(rep(1,n),X) %*% Beta+rnorm(n,0,1)
matop(y, X, bigmat = TRUE)

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