mat.rank: Matrix Rank
In ajabadi/mixOmics2: Omics Data Integration Project

Description Usage Arguments Details Value Author(s) See Also Examples

This function estimate the rank of a matrix.

1	mat.rank(mat, tol)

`mat`	a numeric matrix or data frame that can contain missing values.
`tol`	positive real, the tolerance for singular values, only those with values larger than `tol` are considered non-zero.

mat.rank estimate the rank of a matrix by computing its singular values d[i] (using nipals). The rank of the matrix can be defined as the number of singular values d[i] > 0.

If tol is missing, it is given by tol=max(dim(mat))*max(d)*.Machine$double.eps.

The returned value is a list with components:

`rank`	a integer value, the matrix rank.
`tol`	the tolerance used for singular values.

Sébastien Déjean and Ignacio González.

nipals

## Hilbert matrix
hilbert <- function(n) { i <- 1:n; 1 / outer(i - 1, i, "+") }
mat <- hilbert(16)
mat.rank(mat)

## Not run: 
## Hilbert matrix with missing data
idx.na <- matrix(sample(c(0, 1, 1, 1, 1), 36, replace = TRUE), ncol = 6)
m.na <- m <- hilbert(9)[, 1:6]
m.na[idx.na == 0] <- NA
mat.rank(m)
mat.rank(m.na)

## End(Not run)