MRS (version 1.2.6)

plotTree: Plot nodes of the representative tree

Description

This function visualizes the representative tree of the output of the mrs function. For each node of the representative tree, the posterior probability of difference (PMAP) or the effect size is plotted. Each node in the tree is associated to a region of the sample space. All non-terminal nodes have two children nodes obtained by partitiing the parent region with a dyadic cut along a given direction. The numbers under the vertices represent the cutting direction.

Usage

plotTree(ans, type = "prob", group = 1, legend = FALSE, main = "",
  node.size = 5, abs = TRUE)

Arguments

ans

A mrs object.

type

What is represented at each node. The options are type = c("eff", "prob").

group

If type = "eff", which group effect size is used.

legend

Color legend for type. Default is legend = FALSE.

main

Main title. Default is main = "".

node.size

Size of the nodes. Default is node.size = 5.

abs

If TRUE, plot the absolute value of the effect size. Only used when type = "eff".

References

Soriano J. and Ma L. (2017). Probabilistic multi-resolution scanning for two-sample differences. Journal of the Royal Statistical Society: Series B (Statistical Methodology). tools:::Rd_expr_doi("10.1111/rssb.12180")

Ma L. and Soriano J. (2018). Analysis of distributional variation through multi-scale Beta-Binomial modeling. Journal of Computational and Graphical Statistics. Vol. 27, No. 3, 529-541.. tools:::Rd_expr_doi("10.1080/10618600.2017.1402774")

Examples

set.seed(1)
p = 2
n1 = 200
n2 = 200
mu1 = matrix( c(9,9,0,4,-2,-10,3,6,6,-10), nrow = 5, byrow=TRUE)
mu2 = mu1; mu2[2,] = mu1[2,] + 1

Z1 = sample(5, n1, replace=TRUE)
Z2 = sample(5, n2, replace=TRUE)
X1 = mu1[Z1,] + matrix(rnorm(n1*p), ncol=p)
X2 = mu2[Z2,] + matrix(rnorm(n2*p), ncol=p)
X = rbind(X1, X2)
colnames(X) = c(1,2)
G = c(rep(1, n1), rep(2,n2))

ans = mrs(X, G, K=8)
plotTree(ans, type = "prob", legend = TRUE)