| rm.spacing.distribution {RMThreshold} | R Documentation | 
Plot the empirical distribution of the eigenvalue spacings
Description
A histogram of the empirical distribution of the eigenvalue spacings is plotted. Optionally, curves illustrating the Wigner surmise and/or the Exponential distribution are added.
Usage
 rm.spacing.distribution(ev.spacing, nr.breaks = 51, 
	wigner = TRUE, expo = TRUE, 
	title = "Eigenvalue spacing distribution (NNSD)", 
	threshold = NA, dist.Wigner = NA, 
	dist.Expon = NA, pop.up = TRUE, fn = NULL) 	
Arguments
ev.spacing | 
 A numeric vector containing the spacings of the eigenvalues.  | 
nr.breaks | 
 Number of bins used in the histogram.  | 
wigner | 
 A logical variable that determines if the Wigner-Dyson distribution (Wigner surmise) is to be added to a plot.  | 
expo | 
 A logical variable that determines if the Exponential distribution is to be added to the plot.  | 
title | 
 String containing the title of the plot.  | 
threshold | 
 If not NA, this value will be displayed in the plot, labeled 'threshold'.  | 
dist.Wigner | 
 If not NA, this value will be added to the plot, with a text indicating that it is the numerical value of the Kullback-Leibler distance between the empirical eigenvalue spacing distribution function and the Wigner-Dyson distribution function.  | 
dist.Expon | 
 If not NA, this value will be added to the plot, with a text indicating that it is the numerical value of the Kullback-Leibler distance between the empirical eigenvalue spacing distribution function and the Exponential distribution.  | 
pop.up | 
 A logical variable that determines if the plot is shown in a plot window.  | 
fn | 
 A string determining the filename for storage. Must have extension 'png' or 'pdf'.  | 
Value
The name of the plot filename chosen, or NULL.
Author(s)
Uwe Menzel uwemenzel@gmail.com
See Also
 Plotting the eigenvalue distribution: rm.ev.density
Examples
## Plot histogram of the spacings of the unfolded eigenvalues of a random matrix:
set.seed(777)
random.matrix <- create.rand.mat(size = 1000, distrib = "norm")$rand.matr
res <- rm.ev.unfold(random.matrix)					  
rm.spacing.distribution(res$ev.spacing)