R: Nonparametric transfer

bdgraph.npn {BDgraph} | R Documentation

## Nonparametric transfer

### Description

Transfers non-Gaussian data to Gaussian.

### Usage

     bdgraph.npn( data, npn = "shrinkage", npn.thresh = NULL )

### Arguments

`data` | An (n x p) `matrix` or a `data.frame` corresponding to the data (n is the sample size and p is the number of variables).
`npn` | A character with three options `"shrinkage"` (default), `"truncation"`, and `"skeptic"`. Option `"shrinkage"` is for the shrunken transformation, option `"truncation"` is for the truncated transformation and option `"skeptic"` is for the non-paranormal skeptic transformation. For more details see references.
`npn.thresh` | The truncation threshold; it is only for the truncated transformation (`npn=` `"truncation"`). The default value is 1/(4n^{1/4} √{π \log(n)}).

### Value

An (n \times p) matrix of transferred data, if `npn = "shrinkage" or "truncation"`, and a non-paranormal correlation (p \times p) matrix, if `npn = "skeptic"`.

### Author(s)

Reza Mohammadi a.mohammadi@uva.nl

### References

Liu, H., et al (2012). High Dimensional Semiparametric Gaussian Copula Graphical Models, Annals of Statistics, 40(4):2293-2326

Zhao, T. and Liu, H. (2012). The huge Package for High-dimensional Undirected Graph Estimation in `R`, Journal of Machine Learning Research, 13:1059-1062

### See Also

`bdgraph.sim`, `bdgraph`, `bdgraph.mpl`

### Examples

    ## Not run:
    # Generating multivariate normal data from a 'random' graph
    data.sim <- bdgraph.sim( n = 6, p = 4, size = 4 )
    data     <- ( data.sim $ data - 3 ) ^ 4
    data

    # Transfer the data by truncation
    bdgraph.npn( data, npn = "truncation" )

    # Transfer the data by shrunken
    bdgraph.npn( data, npn = "shrunken" )

    # Transfer the data by skeptic
    bdgraph.npn( data, npn = "skeptic" )

    ## End(Not run)

[Package BDgraph version 2.62 Index]