View source: R/drawpostanalysis.R
drawPostAnalysis | R Documentation |
Plot latent node cluster
drawPostAnalysis( mcmcout, Y, point.cex = 3, text.cex = 3, segment.size = 0.1, n.cluster = NULL, start = 1, frequency = 1 )
mcmcout |
NetworkChange output |
Y |
Input raw data |
point.cex |
node point size. Default is 3. |
text.cex |
node label size. Default is 3. |
segment.size |
segment size. Default is 0.1. |
n.cluster |
number of cluster. Default is 3. |
start |
start of ts object |
frequency |
frequency of ts object |
A plot object
Jong Hee Park and Yunkyun Sohn. 2020. "Detecting Structural Change in Longitudinal Network Data." Bayesian Analysis. Vol.15, No.1, pp.133-157.
## Not run: set.seed(1973) ## generate an array with two constant blocks data(MajorAlly) Y <- MajorAlly fit <- NetworkChange(newY, R=2, m=2, mcmc=G, initial.s = initial.s, burnin=G, verbose=0, v0=v0, v1=v1) drawPostAnalysis(fit, Y, n.cluster=c(4, 4, 3)) ## End(Not run)
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