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Davies (version 1.1-5)

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

Description

A newbie wrapper (and pretty-printer) for maximum.likelihood() and least.squares(). Draws an empirical quantile function (fit.davies.p()) or PDF (fit.davies.q()) and 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

See Also

least.squares , maximum.likelihood

Examples

Run this code
fit.davies.q(rnorm(100)^2)
  fit.davies.p(exp(rnorm(100))) 

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

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