summary.gigFit: Summarizing Normal Inverse Gaussian Distribution Fit

In GeneralizedHyperbolic: The Generalized Hyperbolic Distribution

Summarizing Normal Inverse Gaussian Distribution Fit

Description

summary Method for class "gigFit".

Usage

## S3 method for class 'gigFit'
summary(object, hessian = FALSE,
        hessianMethod = "tsHessian", ...)

## S3 method for class 'summary.gigFit'
print(x,
                               digits = max(3, getOption("digits") - 3), ...)

Arguments

object	An object of class "gigFit", resulting from a call to gigFit.
hessian	Logical. If TRUE the Hessian is printed.
hessianMethod	The two-sided Hessian approximation given by tsHessian from the package DistributionUtils is the only method implemented so far.
x	An object of class "summary.gigFit", resulting from a call to summary.gigFit.
digits	The number of significant digits to use when printing.
...	Further arguments passed to or from other methods.

Details

If hessian = FALSE no calculations are performed, the class of object is simply changed from gigFit to summary.gigFit so that it can be passed to print.summary.gigFit for printing in a convenient form.

If hessian = TRUE the Hessian is calculated via a call to gigHessian and the standard errors of the parameter estimates are calculated using the Hessian and these are added to the original list object. The class of the object returned is again changed to summary.gigFit.

Value

summary.gigFit returns a list comprised of the original object object and additional elements hessian and sds if hessian = TRUE, otherwise it returns the original object. The class of the object returned is changed to summary.gigFit.

See gigFit for the composition of an object of class gigFit.

If the Hessian and standard errors have not been added to the object x, print.summary.gigFit prints a summary in the same format as print.gigFit. When the Hessian and standard errors are available, the Hessian is printed and the standard errors for the parameter estimates are printed in parentheses beneath the parameter estimates, in the manner of fitdistr in the package MASS.

Author(s)

David Scott [e-mail], Christine Yang Dong [e-mail]

See Also

gigFit, summary, gigHessian.

Examples

### Continuing the  gigFit(.) example:
param <- c(1,1,1)
dataVector <- rgig(500, param = param)
fit <- gigFit(dataVector)
print(fit)
summary(fit, hessian = TRUE, hessianMethod = "tsHessian")

GeneralizedHyperbolic documentation built on Nov. 26, 2023, 5:07 p.m.