GraphicalModel: Simulate a covariance matrix from the specific graph (Adj)...

In xueweic/APGD: TGPred: Efficient methods for predicting target genes of a transcription factor by integrating statistics, machine learning, and optimization.

Simulate a covariance matrix from the specific graph (Adj) based on a Gaussian graphical model.

Usage

GraphicalModel(Adj, a1 = -0.7, a2 = -0.1, b1 = 0.1, b2 = 0.7)

Arguments

Adj	the adjacency matrix of network structure
a1,a2,b1,b2	parameters for constructing domain [a1, a2] union [b1, b2] # default: a1 = -0.7, a2 = -0.1, b1 = 0.1, b2 = 0.7

Value

Sigma

the covariance matrix of genes according to network structure.

Examples

## Using "ConstructNetwork" to genarate network
N <- 200
Adj <- ConstructNetwork(N, "BAN")

Sigma1 = GraphicalModel(Adj)

xueweic/APGD documentation built on Sept. 4, 2023, 2:18 a.m.