qqgl
produces a Quantile-Quantile plot of data against the
generalised lambda distribution, or a Q-Q plot to compare two sets of parameter values
for the generalised lambda distribution. It does for the generalised lambda
distribution what qqnorm
does for the normal.
qqgl(y = NULL, lambda1 = 0, lambda2 = NULL, lambda3 = NULL, lambda4 = NULL, param = "fkml", lambda5 = NULL, abline = TRUE, lambda.pars1 = NULL, lambda.pars2 = NULL, param2 = "fkml", points.for.2.param.sets = 4000, ...)
fmkl
or rs
and of length 5 for parameterisation fm5
.
If it is a vector, it gives all the parameters of the generalised lambda
distribution (see below for details) and the other lambda
arguments
must be left as NULL. Alternatively, leave lambda1
as the default value of 0 and use the
lambda.pars1
argument instead.
If it is a a single value, it is $lambda 1$, the location parameter of the distribution and the other parameters are given by the following arguments
Note that the numbering of the $lambda$ parameters for the fmkl parameterisation is different to that used by Freimer, Mudholkar, Kollia and Lin.
fmkl
uses Freimer, Mudholkar, Kollia and Lin (1988) (default).
rs
uses Ramberg and Schmeiser (1974)
fm5
uses the 5 parameter version of the FMKL parameterisation
(paper to appear)lambda1
to lambda4
for details.lambda1
to lambda4
for details. Use
lambda.pars1
and lambda.pars2
to produce a QQ plot comparing
two generalised lambda distributionsqqplot
qqline
gld
for more details on the Generalised Lambda
Distribution. A Q-Q plot provides a way to visually assess the
correspondence between a dataset and a particular distribution, or between two
distributions.
gld
,starship
qqgl(rgl(100,0,1,0,-.1),0,1,0,-.1)
qqgl(lambda1=c(0,1,0.01,0.01),lambda.pars2=c(0,.01,0.01,0.01),param2="rs",pch=".")
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