| summary.vgFit | R Documentation |
summary Method for class "vgFit".
## S3 method for class 'vgFit'
summary(object, ...)
## S3 method for class 'summary.vgFit'
print(x, digits = max(3, getOption("digits") - 3), ...)
object |
An object of class |
x |
An object of class |
digits |
The number of significant digits to use when printing. |
... |
Further arguments passed to or from other methods. |
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.
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.
vgFit, summary.
### Continuing the vgFit(.) example:
param <- c(0,0.5,0,0.5)
dataVector <- rvg(500, param = param)
fit <- vgFit(dataVector)
print(fit)
summary(fit)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.