plotTree: Plot nodes of the representative tree

Description Usage Arguments Note References Examples

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

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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".

Note

The package igraph is required.

References

Soriano J. and Ma L. (2016). Probabilistic multi-resolution scanning for two-sample differences. Journal of the Royal Statistical Society: Series B (Statistical Methodology). http://onlinelibrary.wiley.com/doi/10.1111/rssb.12180/abstract

Ma L. and Soriano J. (2016). Analysis of distributional variation through multi-scale Beta-Binomial modeling. arXiv. http://arxiv.org/abs/1604.01443

Examples

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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)

jacsor/MRS documentation built on May 18, 2019, 9:05 a.m.