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MRS (version 1.1)

plot1D: Plot regions of the representative tree in 1D

Description

This function visualizes the regions of the representative tree of the output of the mrs function. For each region the posterior probability of difference (PMAP) or the effect size is plotted.

Usage

plot1D(ans, type = "prob", group = 1, dim = 1, regions = rep(1, length(ans$RepresentativeTree$Levels)), legend = FALSE, main = "default")

Arguments

ans
An mrs object.
type
What is represented at each node. The options are type = c("eff", "prob"). Default is type = "prob".
group
If type = "eff", which group effect size is used. Default is group = 1.
dim
If the data are multivariate, dim is the dimension plotted. Default is dim = 1.
regions
Binary vector indicating the regions to plot. The default is to plot all regions.
legend
Color legend for type. Default is legend = FALSE.
main
Overall title for the plot.

References

Soriano J. and Ma L. (2014). Multi-resolution two-sample comparison through the divide-merge Markov tree. Preprint. http://arxiv.org/abs/1404.3753

Examples

Run this code
set.seed(1)
p = 1
n1 = 200
n2 = 200
mu1 = matrix( c(0,10), nrow = 2, byrow = TRUE)
mu2 = mu1; mu2[2] = mu1[2] + .01
sigma = c(1,.1)

Z1 = sample(2, n1, replace=TRUE, prob=c(0.9, 0.1))
Z2 = sample(2, n2, replace=TRUE, prob=c(0.9, 0.1))
X1 = mu1[Z1] + matrix(rnorm(n1*p), ncol=p)*sigma[Z1]
X2 = mu2[Z2] + matrix(rnorm(n2*p), ncol=p)*sigma[Z1]
X = rbind(X1, X2)
G = c(rep(1, n1), rep(2,n2))

ans = mrs(X, G, K=10)
plot1D(ans, type = "prob")
plot1D(ans, type = "eff")

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