| summary.skewhypFit {SkewHyperbolic} | R Documentation |
Summarising the Skew Hyperbolic Student t-Distribution Fit
Description
summary Method for class "skewhypFit".
Usage
## S3 method for class 'skewhypFit'
summary(object, ...)
## S3 method for class 'summary.skewhypFit'
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.skewhypFit calculates standard errors for errors for
the estimates of \mu, \delta, \beta
and \nu of the skew hyperbolic Student
t-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
\mu, \log(\delta), \beta and
\log(\nu) the delta method is used to obtain standard
errors for \delta and \nu
Value
If the Hessian is available summary.skewhyhpFit computes
standard errors of \mu, \delta, \beta
and \nu, and adds them to object as
object$sds. Otherwise, no calculations are performed and the
composition object is unaltered.
summary.skewhypFit invisibly returns x with class
changed to summary.skewhypFit.
See skewhypFit for the composition of an object of class
skewhypFit.
print.summary.skewhypFit prints a summary in the same format as
print.skewhypFit 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.
Author(s)
David Scott d.scott@auckland.ac.nz, Fiona Grimson
References
Aas, K. and Haff, I. H. (2006). The Generalised Hyperbolic Skew Student's t-distribution, Journal of Financial Econometrics, 4, 275–309.
See Also
Examples
## Continuing the skewhypFit(.) example:
data(lrdji)
djfit <- skewhypFit(lrdji, print = FALSE, plot = FALSE, hessian = TRUE)
print(djfit)
summary(djfit)