SimHetDat: Simulate Heterogeneous Data for Gaussian Graphical Models

In GGMM: Mixture Gaussian Graphical Models

Description

Simulate Heterogeneous data with a band structure, which can be used in GGMM(data,...) for estimating the structure of the Gaussian graphical network.

Usage

SimHetDat(n = 100, p = 200, M = 3, mu = 0.3, type = "band")

Arguments

n	Number of observations for each group, default of 100.
p	Number of covariates for each observation, default of 200.
M	Number of latent groups for the simulated dataset choose 2 or 3, default of 3.
mu	The mean difference among groups. If M=3, the mean of three groups are -mu,0,mu, respectively. If M=2, the mean of two groups are 0,mu, respectively.
type	type=="band" which denotes the band structure, with precision matrix C_{i,j}=≤ft\{\begin{array}{ll} 0.5,&\textrm{if $≤ft| j-i \right|=1, i=2,...,(p-1),$}\\ 0.25,&\textrm{if $≤ft| j-i \right|=2, i=3,...,(p-2),$}\\ 1,&\textrm{if $i=j, i=1,...,p,$}\\ 0,&\textrm{otherwise.} \end{array}\right.

Value

data	nxp Heterogeneous Gaussian distributed data.
A	pxp adjacency matrix used for generating data.
label	The group indices for each observation.

Author(s)

Bochao [e-mail] and Faming Liang

References

Liang, F., Song, Q. and Qiu, P. (2015). An Equivalent Measure of Partial Correlation Coefficients for High Dimensional Gaussian Graphical Models. J. Amer. Statist. Assoc., 110, 1248-1265.

Examples

library(GGMM)
SimHetDat(n = 100, p = 200, M = 3, mu = 0.5, type = "band")

GGMM documentation built on May 1, 2019, 9:36 p.m.