plot1D: Plot regions of the representative tree in 1D

In MRS: Multi-Resolution Scanning for Cross-Sample Differences

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",
  abs = TRUE)

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

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

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")

Example output

MRS documentation built on May 2, 2019, 1:51 a.m.