plot1D {MRS} | R Documentation |
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",
abs = TRUE)
Arguments
ans |
An |
type |
What is represented at each node.
The options are |
group |
If |
dim |
If the data are multivariate, |
regions |
Binary vector indicating the regions to plot. The default is to plot all regions. |
legend |
Color legend for type. Default is |
main |
Overall title for the plot. |
abs |
If |
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). 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.. doi:10.1080/10618600.2017.1402774
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")