qqgl
produces a Quantile-Quantile plot of data against the
quantile-based skew logistic distribution,
or a Q-Q plot to compare two sets of parameter values
for the quantile-based skew logistic distribution. This function does for the
skew logistic distribution what qqnorm
does for the normal.
qqsl(y=NULL,parameters1,parameters2=NULL,abline=TRUE,
granularity.for.2.dists=4000,use.endpoints=FALSE,...)
The data sample
A vector of length 3, containg the parameters of the skew logistic distribution, \(\alpha\), \(\beta\) and \(\delta\).
Second set of parameters of the skew logistic distribution. A vector of length 3, as described above for parameters1
.
A logical value, TRUE adds a line through the origian with a slope of 1 to the plot
Number of quantiles to use in a Q-Q plot comparing two sets of parameter values
logical. When comparing two sets of parameter values, should Q(0) and Q(1) be used? TRUE will give QQ plots including the theoretical
minimum and maximum of the distribution, which is arguably not equivalent to
what would be seen in QQ plots based on data. FALSE will give QQ plots based on
ideal depths (type 8 quantiles, see quantile
documentation), where n
is the granularity.for.2.dists
.
graphical parameters, passed to qqplot
A list of the same form as that returned by qqline
The x coordinates of the points that were/would be plotted, corresponding to a skew logistic distibution with parameters \(\alpha\), \(\beta\) and \(\delta\).
The original y
vector, i.e., the corresponding y
coordinates, or a corresponding set of quantiles from a skew logistic
distribution with the second set of parameters
See sld
for more details on the Skew Logistic
Distribution. A Q-Q plot provides a way to visually assess the
correspondence between a dataset and a particular distribution, or between two
distributions.
van Staden, P.J. and King, R.A.R. (2015) The quantile-based skew logistic distribution, Statistics and Probability Letters 96 109--116. 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
# NOT RUN {
qqsl(y=rsl(100,c(0,1,0.7)),parameters1=c(0,1,0.7))
qqsl(parameters1=c(0,1,0.7),parameters2=c(0,0.9,0.5),col="blue")
# }
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