fit.davies.p: Fits and plots Davies distributions to datasets

In Davies: The Davies Quantile Function

Fits and plots Davies distributions to datasets

Description

A convenience wrapper (and pretty-printer) for maximum.likelihood() and least.squares(). Given a dataset, it draws an empirical quantile function (fit.davies.p()) or PDF (fit.davies.q()) and superimposes the dataset.

Usage

fit.davies.p(x , print.fit=FALSE, use.q=TRUE , params=NULL, small=1e-5 , ...)
fit.davies.q(x , print.fit=FALSE, use.q=TRUE , params=NULL, ...)

Arguments

x	dataset to be fitted and plotted
print.fit	Boolean with TRUE meaning print details of the fit
use.q	Boolean with TRUE meaning use least.squares() (rather than maximum.likelihood())
params	three-element vector holding the three parameters of the davies dataset. If NULL, determine the parameters using the method indicated by use.q
small	small positive number showing range of quantiles to plot
...	Additional parameters passed to plot()

Value

If print.fit is TRUE, return the optimal parameters

Author(s)

Robin K. S. Hankin

See Also

least.squares , maximum.likelihood

Examples

  fit.davies.q(rchisq(100,1))
  fit.davies.p(exp(rnorm(100))) 

  data(x00m700p4)
  fit.davies.q(x00m700p4)

Davies documentation built on March 18, 2022, 5:52 p.m.