RMThreshold-internal: Internal functions for the RMThreshold package

In RMThreshold: Signal-Noise Separation in Random Matrices by using Eigenvalue Spectrum Analysis

Description

Internal functions for the RMThreshold package

Usage

kb.distance(histo) 
rm.exp.distrib(x)
kld(observed, expected, plot) 
rm.get.file.extension(plotnames)
rm.ev.unfold(rand.mat, unfold.method, bandwidth, nr.fit.points, 
			discard.outliers, fn, pop.up, silent)  
rm.spacing.scatter(ev.spacing, title, pop.up, fn) 
rm.trapez.int(x, y)
rm.reorder.ev(eigenvalues, eigenvec) 
rm.get.sparseness(mat) 
wigner.surmise(x)
wigner.semi.circle(x)
rm.get.distance(ev.spacing, dist.method, nr.breaks)
rm.likelihood.plot(thresholds, log.le, log.lw, smooth.par, fn, interactive)
rm.distance.plot(thresholds, dist.Expon, dist.Wigner, smooth.par, fn, interactive)
rm.unfold.gauss(eigenvalues, bandwidth, fn, pop.up, silent)
rm.unfold.spline(eigenvalues, nr.fit.points, fn, pop.up)
rm.sse(ev.spacing, bandwidth, nr.points, N)
rm.show.test(thresholds, p.values, main, fn, interactive)
rm.sse.plot(thresholds, sse.values, main, fn, interactive)

Arguments

nr.fit.points	Number of supporting points used for the cubic spline to the empirical cumulative distribution function.
discard.outliers	A logical variable that determines if outliers are discarded from the spectrum of eigenvalues.
silent	A logical variable that decides if a function outputs runtime messages or not.
histo	An R object of class 'histogram'. Output of the hist function.
x	A real-valued number.
eigenvalues	A numerical vector containing the eigenvalues of a matrix.
wigner	A logical variable that determines if the Wigner semi-circle or the Wigner surmise is added to a plot.
title	String variable containing the title of a plot.
pop.up	A logical variable that determines if a plot window is supposed tp pop up during function execution.
fn	A filename.
observed	A numerical vector with the observed frequency of eigenvalues in each bin of the distribution function.
expected	A numerical vector with the expected frequency of eigenvalues in each bin. The expected values refer to a limiting distribution, either Wigner-Dyson or Exponential distribution.
plot	A logical variable that determines if a plot should be created.
plotnames	A string or character vector of filenames for plots to be viewed.
rand.mat	A symmetric, real-valued random matrix.
fit	Name of the plot showing the cubic spline fit to the cumulative distribution. No plot will be made if fit = NULL
ev.spacing	A vector with the normalized eigenvalue spacings of a random matrix.
y	A numerical vector defining the y-values of a function.
eigenvec	A matrix containing the eigenvectors of a matrix (in columns).
mat	A real-valued matrix.
nr.breaks	Number of bins used in the histogram to subdivide the empirical eigenvalue spacing distribution.
log.le	Log likelihood of the observed eigenvalue distances when an exponential distribution is assumed.
log.lw	Log likelihood of the observed eigenvalue distances when a Wigner-Dyson distribution is assumed.
smooth.par	Parameter controlling the degree of smoothing in the loess regression curve presented in the final plot (distance vs. threshold).
interactive	A logical variable that determines if thresholds can be chosen by mouse clicks in the final plot (distance vs. threshold).
bandwidth	Bandwidth used to calculate the Gaussian kernel density. See description of the density function.
unfold.method	A string that decides which method is used for eigenvalue unfolding. One of 'gaussian' or 'spline'.
dist.method	A string that determines which method is used to estimate the distance to the limiting distributions. One of 'LL' (Log Likelihood) or 'KLD' (Kullback-Leibler Distance).
thresholds	A numerical vector containing the values of the thresholds probed in the main function (rm.get.threshold).
dist.Expon	A numerical vector containing the estimated distances to the Exponential distribution calculated in the main function (rm.get.threshold).
dist.Wigner	A numerical vector containing the estimated distances to the Exponential distribution calculated in the main function (rm.get.threshold).
p.values	A numerical vector containing the p-values for a significance test.
sse.values	A numerical vector containing the Sum of Squared Errors between observed NNSD and Exponential function.
nr.points	Number of supporting points used to approximate the density function.
N	Number of sections used to calculate the Sum of Squared Errors (SSE).
main	String variable containing the title of a plot.

Details

These functions are not intended to be called by the user.

RMThreshold documentation built on May 2, 2019, 8:51 a.m.