# gsorth

From matlib v0.9.2
by Michael Friendly

##### Gram-Schmidt Orthogonalization of a Matrix

Calculates a matrix with uncorrelated columns using the Gram-Schmidt process

##### Usage

`gsorth(y, order, recenter = TRUE, rescale = TRUE, adjnames = TRUE)`

##### Arguments

- y
a numeric matrix or data frame

- order
if specified, a permutation of the column indices of

`y`

- recenter
logical; if

`TRUE`

, the result has same means as the original`y`

, else means = 0 for cols 2:p- rescale
logical; if

`TRUE`

, the result has same sd as original, else, sd = residual sd- adjnames
logical; if

`TRUE`

, colnames are adjusted to Y1, Y2.1, Y3.12, ...

##### Details

This function, originally from the heplots package has now been deprecated in matlib. Use
`GramSchmidt`

instead.

##### Value

a matrix/data frame with uncorrelated columns

##### Examples

```
# NOT RUN {
set.seed(1234)
A <- matrix(c(1:60 + rnorm(60)), 20, 3)
cor(A)
G <- gsorth(A)
zapsmall(cor(G))
# }
```

*Documentation reproduced from package matlib, version 0.9.2, License: GPL (>= 2)*

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