CGM: Joint Estimation of Multiple Graphical Models

In Weilin23/CGM: Joint Estimation of Multiple Graphical Models

Description

The method in paper Joint Estimation of Multiple Graphical Models. A method which jointly estimates several graphical models corresponding to the different categories present in the data. The method aims to preserve the common structure, while allowing for differences between the categories.

Usage

CGM_AHP_train <- function(trainX, trainY, lambda_value, adaptive_weight=array(1, c(length(unique(Y)), ncol(X), ncol(X))))

Examples

print("this is a test for CGM_AHP_train")
X = matrix(rnorm(50*20),ncol=20)
Y <- NULL
ps <- cumsum(c(0.25,0.25,0.25,0.25))
r <- runif(50)
x <- c(1,2,3,4)
for (i in 1:50) Y <- c(Y, x[which(r[i] <= ps)[1]])
trainX = X
trainY = Y
lbd = 0.001
result = CGM_AHP_train(trainX, trainY, lbd)

Weilin23/CGM documentation built on Oct. 31, 2019, 1:13 a.m.