VisCov (version 1.5.0)

panelSelectMultiple: Selecting Panels From Several Distributions

Description

To draw the selected panels from several distributions generated by VisCov.

Usage

panelSelectMultiple(selected.condition, CovPlotDataMultiple, 
                    range.logical.contour = FALSE, range.logical.all = TRUE,
                    row = FALSE)

Value

No return value, called for side effects.

Arguments

selected.condition

a vector of strings containing types of the panels that one wishes to select: For layer 1, "vari", "cor"; for layer 2, "scatter1", "scatter2", "scatter3", "scatter4", "scatter5"; for layer 3, "contour", "threeD"; for layer 4, "Effective.Variance", "Effective.Dependence", "Effective.Dependence.submatrix".

CovPlotDataMultiple

a list of objects returned by VisCov.

range.logical.all

a logical value indicating whether the ranges in the panels are set as the same over different sets of samples. For the histograms, the ranges of frequencies are set as the same over the different sets of samples.

range.logical.contour

a logical value indicating whether the ranges of the contour plots are set as the same over different sets of samples when range.logical.all is TRUE.

row

a logical value whether the panels belonging to the same set of samples are arranged in the same row. If it is FALSE, they are arranged in the same column.

References

Tokuda, T., Goodrich, B., Van Mechelen, I., Gelman, A. and Tuerlinckx, F. (submitted). Visualizing Distributions of Covariance Matrices.

Examples

set.seed(1234)
distribution = "Inverse Wishart"
dim = 4
param = list(prob = 0.5, dim = dim, nu = dim+1, scaleCov = diag(1,dim))
CovPlotData1 = VisCov(distribution, param, title.logical = FALSE)
distribution = "Inverse Wishart"
dim = 4
param = list(prob = 0.5, dim = dim, nu = dim+50, scaleCov = diag(1,dim))
CovPlotData2 = VisCov(distribution, param, title.logical = FALSE)
selected.condition = c("scatter1", "scatter4", "contour", "Effective.Dependence")
panelSelectMultiple(selected.condition, list(CovPlotData1, CovPlotData2))