| summary.hyperbFit {HyperbolicDist} | R Documentation |
Summarizing Hyperbolic Distribution Fit
Description
summary Method for class "hyperbFit".
Usage
## S3 method for class 'hyperbFit'
summary(object, ...)
## S3 method for class 'summary.hyperbFit'
print(x, digits = max(3, getOption("digits") - 3), ...)
Arguments
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. |
Details
summary.hyperbFit calculates standard errors for the estimates
of \pi, \zeta, \delta, and
\mu of the hyperbolic distribution parameter vector Theta if
the Hessian from the call to optim or nlm
is available. Because the parameters in the call to the optimiser are
\pi, \log(\zeta),
\log(\delta), and \mu, the delta method is
used to obtain the standard errors for \zeta and
\delta.
Value
If the Hessian is available, summary.hyperbFit computes
standard errors for the estimates of \pi, \zeta,
\delta, and \mu, and adds them to object
as object$sds. Otherwise, no calculations are performed and the
composition of object is unaltered.
summary.hyperbFit invisibly returns x
with class changed to summary.hyperbFit.
See hyperbFit for the composition of an object of class
hyperbFit.
print.summary.hyperbFit prints a summary in the same format as
print.hyperbFit 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.
See Also
Examples
### Continuing the hyperbFit(.) example:
Theta <- c(2,2,2,2)
dataVector <- rhyperb(500, Theta)
fit <- hyperbFit(dataVector, method = "BFGS", hessian = TRUE)
print(fit)
summary(fit)