heatmap_fit: summary plot of globally and pairwise informative variables

Description

Heatmaps of the data with estimated informative variables and the indicator for pairwise informativeness of each globally informative variables.

Usage

heatmap_fit(output, y, plot_type = 'info.data', eps.diff = 1e-5,
margins = c(5,5), cexRow = 0.5, cexCol = 0.4, lhei = c(0.8,5),
lwid=c(0.8,5), adjCol = c(0.8,0.4), sepwidth=c(0.05,0.05))

Arguments

output

results from parse, apfp, apL1 or nopenalty functions. For the `nopenalty' function, the `short.output' should be FALSE.

data.

plot_type

takes two values, 'info.data' or 'info.pair'. 'info.data' is the heatmap of the data with informative variables; 'info.pair' indicates which globally informative variable is pairwise informative for each pair of clusters.

eps.diff

The lower bound of pairwise difference of two mean values. Any value lower than it is treated as 0. The default value is 1e-5.

margins

parameter in 'heatmap.2' function, 2-dimensional numeric vector containing the margins for column and row names, respectively.

cexRow

parameter in 'heatmap.2' function, positive numbers for the row axis labeling.

cexCol

parameter in 'heatmap.2' function, positive numbers for the column axis labeling.

lhei

parameters in 'heatmap.2' function, visual layout of column height.

lwid

parameters in 'heatmap.2' function, visual layout of column weight.

adjCol

parameters in 'heatmap.2' function, justification of column labels (variables names).

sepwidth

parameters in 'heatmap.2' function, 2-dimensional vector giving the width and height of the separator box

Value

heatmap of the data with informative variables or heatmap of whether the globally informative variables are pairwise informative for each pair of clusters or not.

References

Gregory R. Warnes, Ben Bolker, Lodewijk Bonebakker, Robert Gentleman, Wolfgang Huber Andy Liaw, Thomas Lumley, Martin Maechler, Arni Magnusson, Steffen Moeller, Marc Schwartz and Bill Venables (2015). gplots: Various R Programming Tools for Plotting Data. R package version 2.17.0. https://CRAN.R-project.org/package=gplots

Examples

Run this code

y <- rbind(matrix(rnorm(120,0,1),ncol=4),
matrix(rnorm(120,4,1), ncol=4), matrix(rnorm(120,0,1),ncol=4))
output <- parse(K = 3, lambda = 1, y=y)
output$mu.hat.best
heatmap_fit(output, y, cexRow=1)