GLDEX (version 2.0.0.9.3)

qqplot.gld: Do a quantile plot on the univariate distribution fits.

Description

This plots the theoretical and actual data quantiles to allow the user to examine the adequacy of a single gld distribution fit.

Usage

qqplot.gld(data, fit, param, len = 10000, name = "", 
corner = "topleft",type="",range=c(0,1),xlab="",main="")

Value

A plot is given.

Arguments

data

Data fitted.

fit

Parameters of distribution fit.

param

Can be either "rs" or "fmkl".

len

Precision of the quantile calculatons. Default is 10000. This means 10000 points are taken from 0 to 1.

name

Name of the data set, added to the title of plot if main is missing.

corner

Can be "bottomright", "bottom", "bottomleft", "left", "topleft", "top", "topright", "right", "center" as in legend.

type

This can be "" or "str.qqplot", the first produces the raw quantiles and the second plot them on a straight line. Default is "".

range

This is the range for which the quantiles are to be plotted. Default is c(0,1).

xlab

x axis label, if left blank, then default is "Data".

main

Title of the plot, if left blank, a default title will be added.

Author

Steve Su

See Also

qqplot.gld.bi

Examples

# \donttest{
 set.seed(1000)

 junk<-rweibull(300,3,2)

# Fit the function using fun.data.fit.ml
 obj.fit1.ml<-fun.data.fit.ml(junk)

# Do a quantile plot on the raw quantiles
 qqplot.gld(junk,obj.fit1.ml[,1],param="rs",name="RS ML fit")

# Or a qq plot to examine deviation from straight line
 qqplot.gld(junk,obj.fit1.ml[,1],param="rs",name="RS ML fit",type="str.qqplot")
# }