summary.vgFit: Summarizing Variance Gamma Distribution Fit

Description

summary Method for class "vgFit".

Usage

# S3 method for vgFit
summary(object, ...)
# S3 method for summary.vgFit
print(x, digits = max(3, getOption("digits") - 3), ...)

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.

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.

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 $\nu$.

Examples

Run this code

### Continuing the  vgFit(.) example:
param <- c(0,0.5,0,0.5)
dataVector <- rvg(500, param = param)
fit <- vgFit(dataVector)
print(fit)
summary(fit)