histCausalPaths: Plot histogrames of causal effects.

In andreamrau/GBNcausal: Causal estimation for Gaussian Bayesian networks

Description

The function plots histograms for all direct effects or total effects values through the run.

Usage

histCausalPaths(alphaRes, trueW)

Arguments

alphaRes	matrix - The ith line is a vector of values of a matrix of causal effects, direct or total. Such results can be obtained by applying the causalEffects function to a full.run of a MCMC.GBN run.
trueW	matrix - The real matrix of causal effects.

Value

The function plots histograms for all direct effects or total effects values through the run.

If there is p nodes, there will be p*p histograms.

Examples

# Data creation

seed = 1990
n = 3000
p <- 10
m<-rep(0,10)
sigma<-rep(0.1,10) 

W <- 1*upper.tri(matrix(0,p,p))

data <- dataCreate(nbData = 2*p, p = 10,KO = list(1,9), nbKO = c(p,p), W = W , m = m,sigma = sigma, seed = seed)$data

# Initial Value

W1=1*upper.tri(matrix(0,p,p)) 
m1=rep(0,p)
s1=rep(10e-4,p)
colnames(W1)=names(m1)=names(s1)=rownames(W1)=paste("N",1:p,sep="")

firstGBN = new("GBNetwork",WeightMatrix=W1,resMean=m1,resSigma=s1)
firstGBN = GBNmle(firstGBN,data,lambda= 0,sigmapre=s1)$GBN

# Algorithm

results=MCMC.GBN(data, firstGBN, nbSimulation=2000, burnIn=20, seq=1, verbose=TRUE,verbose.index=100, 
              alpha=1,lambda=0) 
			  
alphaRes <- causalEffects(results$full.run)$alphaRes
histCausalPaths(alphaRes,W)

andreamrau/GBNcausal documentation built on May 12, 2019, 3:34 a.m.