Description Usage Arguments Details Value Author(s) References See Also Examples
Produces plots of density and distribution function for the quantile based skew
logistic distribution. Although you could use curve(dsl(x))
to do this, the fact that the density and quantiles of this distribution are
defined in terms of the depth, u, means that a seperate function that
uses the depths to produce the values to plot is more accurate and efficient.
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parameters |
A vector of length 3, giving the parameters of the quantile-based skew logistic distribution. The 3 elements are alpha (location), beta (scale) and delta (skewing). alpha can take on any real value, beta can take on any positive value and delta must satisfy 0 <= delta <= 1. delta = 0.5 gives the logistic distribution, delta = 0 gives the reflected exponential distribution and delta = 1 gives the exponential distribution. |
add |
Should this add to an existing plot (using |
granularity |
Number of points at which quantiles and density will be calculated.— see details |
xlab |
X axis label |
ylab |
Y axis label |
quant.probs |
Quantiles of distribution to return (see value below). Set to NULL to suppress this return entirely. |
... |
arguments that get passed to |
The quantile-based skew logistic distribution is defined by its quantile
function. The density of the distribution is available explicitly as a
function of depths, u, but not explicitly available as a function of
x (except for the special cases at delta=0,0.5 and 1).
This function calculates quantiles and density as a function of depths to
produce a density plot plotsld
or cumulative probability plot
plotslc
.
A number of quantiles from the distribution, the default being the minimum, maximum and quartiles.
Robert King, [email protected], http://tolstoy.newcastle.edu.au/~rking/
van Staden, P.J. and King, Robert A.R. (2015) The quantile-based skew logistic distribution, Statistics and Probability Letters 96, 109–116. http://dx.doi.org/10.1016/j.spl.2014.09.001
van Staden, Paul J. 2013 Modeling of generalized families of probability distribution in the quantile statistical universe. PhD thesis, University of Pretoria. http://hdl.handle.net/2263/40265
http://tolstoy.newcastle.edu.au/rking/SLD/SLD.html
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