View source: R/summary.hyperbFit.R
| summary.hyperbFit | R Documentation |
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 |
hessian |
Logical. If |
hessianMethod |
Two methods are available to calculate the
Hessian exactly ( |
x |
An object of class |
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)
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