summary.nigFit: Summarizing Normal Inverse Gaussian Distribution Fit

Description

summary Method for class "nigFit".

Usage

# S3 method for nigFit
summary(object, hessian = FALSE,
        hessianMethod = "tsHessian", ...)
# S3 method for summary.nigFit
print(x,
                               digits = max(3, getOption("digits") - 3), ...)

Arguments

object

An object of class "nigFit", resulting from a call to nigFit.

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.

An object of class "summary.nigFit", resulting from a call to summary.nigFit.

digits

The number of significant digits to use when printing.

…

Further arguments passed to or from other methods.

Value

summary.nigFit 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.nigFit.

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

If the Hessian and standard errors have not been added to the object x, print.summary.nigFit prints a summary in the same format as print.nigFit. 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.

Details

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

If hessian = TRUE the Hessian is calculated via a call to nigHessian 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.nigFit.

Examples

Run this code

# NOT RUN {
### Continuing the  nigFit(.) example:
param <- c(2, 2, 2, 1)
dataVector <- rnig(500, param = param)
fit <- nigFit(dataVector, method = "BFGS")
print(fit)
summary(fit, hessian = TRUE, hessianMethod = "tsHessian")
# }