panelSelectMultiple {VisCov} | R Documentation |
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)
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 |
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
|
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. |
Value
No return value, called for side effects.
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))