# bdgraph.npn: Nonparametric transfer In BDgraph: Bayesian Structure Learning in Graphical Models using Birth-Death MCMC

## Description

Transfers non-Gaussian data to Gaussian.

## Usage

 1  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".

## 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

bdgraph.sim, bdgraph, bdgraph.mpl

## Examples

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 ## 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) 

### Example output

Loading required package: Matrix

Attaching package: 'igraph'

The following objects are masked from 'package:stats':

decompose, spectrum

The following object is masked from 'package:base':

union

Attaching package: 'BDgraph'

The following object is masked from 'package:igraph':

compare

[,1]      [,2]      [,3]     [,4]
[1,]  60.53339  24.81089  35.13741 38.66537
[2,]  85.56664  31.71818 142.05419 57.07015
[3,]  85.51874  18.62196  26.25032 29.75299
[4,]  76.34863  40.77787  91.57774 45.82684
[5,]  40.98130  38.23718  39.72276 62.60757
[6,] 100.19918 102.52265  78.00717 30.17403
[,1]       [,2]       [,3]       [,4]
[1,] -0.4752025 -0.4752025 -0.4752025  0.0000000
[2,]  1.0673137  0.0000000  1.6504720  1.0673137
[3,]  0.4752025 -1.0673137 -1.0673137 -1.0673137
[4,]  0.0000000  1.0673137  1.0673137  0.4752025
[5,] -1.0673137  0.4752025  0.0000000  1.6504720
[6,]  1.6504720  1.6504720  0.4752025 -0.4752025
[,1]      [,2]      [,3]     [,4]
[1,]  60.53339  24.81089  35.13741 38.66537
[2,]  85.56664  31.71818 142.05419 57.07015
[3,]  85.51874  18.62196  26.25032 29.75299
[4,]  76.34863  40.77787  91.57774 45.82684
[5,]  40.98130  38.23718  39.72276 62.60757
[6,] 100.19918 102.52265  78.00717 30.17403
[,1]      [,2]      [,3]       [,4]
[1,]  1.0000000 0.2684665 0.3865118 -0.5031735
[2,]  0.2684665 1.0000000 0.6180340  0.2684665
[3,]  0.3865118 0.6180340 1.0000000  0.5608548
[4,] -0.5031735 0.2684665 0.5608548  1.0000000


BDgraph documentation built on May 3, 2021, 9:08 a.m.