fit.davies.p {Davies} | R Documentation |
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
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, ...)
x |
dataset to be fitted and plotted |
print.fit |
Boolean flag with TRUE meaning print details of the fit |
use.q |
Boolean flag 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 |
is.sorted |
Boolean flag with TRUIE meaning that dataset
is sorted from lowest to highest |
small |
small positive number showing range of quantiles to plot |
... |
Additional parameters passed to plot() |
If print.fit
is TRUE, return the optimal parameters
Robin K. S. Hankin
least.squares
, maximum.likelihood
fit.davies.q(rnorm(100)^2) fit.davies.p(exp(rnorm(100))) data(x00m700p4) fit.davies.q(x00m700p4)