summary.vgFit: Summarizing Variance Gamme Distribution Fit
Description
summary Method for class "vgFit".
Usage
## S3 method for class 'vgFit':
summary(object, ...)
## S3 method for class 'summary.vgFit':
print(x, digits = max(3, getOption("digits") - 3), ...)
Arguments
object
An object of class "vgFit", resulting from a call to
vgFit.
x
An object of class "summary.vgFit", resulting from a call to
summary.vgFit.
digits
The number of significant digits to use when printing.
...
Further arguments passed to or from other methods.
Value
If the Hessian is available, summary.vgFit computes
standard errors for the estimates of $c$, $\sigma$,
$\theta$, and $\nu$, and adds them to object
as object$sds. Otherwise, no calculations are performed and the
composition of object is unaltered.
summary.vgFit invisibly returns x with class changed to
summary.vgFit.
See vgFit for the composition of an object of class
vgFit.
print.summary.vgFit prints a summary in the same format as
print.vgFit when the Hessian is not available from
the fit. When the Hessian is available, the standard errors for the
parameter estimates are printed in parentheses beneath the parameter
estimates, in the manner of fitdistr in the package
MASS.
Details
summary.vgFit calculates standard errors for the estimates
of $c$, $\sigma$, $\theta$, and
$\nu$ of the variance gamma distribution parameter vector param if
the Hessian from the call to optim or nlm
is available. Because the parameters in the call to the optimiser are
$c$, $\log(\sigma)$, $\theta$ and
$\log(\nu)$, the delta method is used to obtain the
standard errors for $\sigma$ and $\nu$.