Summarizing Hyperbolic Distribution Fit
summary Method for class "hyperbFit".
## S3 method for class 'hyperbFit' summary(object, hessian = FALSE, hessianMethod = "exact", ...) ## S3 method for class 'summary.hyperbFit' print(x, digits = max(3, getOption("digits") - 3), ...)
object: An object of class "hyperbFit", resulting from a call to hyperbFit.hessian: Logical. If TRUE the Hessian is printed.hessianMethod: Two methods are available to calculate the Hessian exactly ("exact") or approximately ("tsHessian").x: An object of class "summary.hyperbFit", resulting from a call to summary.hyperbFit.digits: The number of significant digits to use when printing....: Further arguments passed to or from other methods.If hessian = FALSE no calculations are performed, the class of object is simply changed from hyperbFit to summary.hyperbFit so that it can be passed to print.summary.hyperbFit for printing in a convenient form.
If hessian = TRUE the Hessian is calculated via a call to hyperbHessian 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.hyperbFit.
summary.hyperbFit 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.hyperbFit.
See hyperbFit for the composition of an object of class hyperbFit.
If the Hessian and standard errors have not been added to the object x, print.summary.hyperbFit prints a summary in the same format as print.hyperbFit. 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.
David Scott d.scott@auckland.ac.nz , Christine Yang Dong c.dong@auckland.ac.nz
hyperbFit, summary, hyperbHessian, tsHessian.
### Continuing the hyperbFit(.) example: param <- c(2, 2, 2, 1) dataVector <- rhyperb(500, param = param) fit <- hyperbFit(dataVector, method = "BFGS") print(fit) summary(fit, hessian = TRUE)