summary.gnlFit: Summarizing Generalised Normal Laplace Distribution Fit
In sjp/NormalLaplace: The Normal Laplace Distribution

Description Usage Arguments Details Value See Also Examples

summary Method for class "gnlFit".

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

`object`	An object of class `"gnlFit"`, resulting from a call to `gnlFit`.
`x`	An object of class `"summary.gnlFit"` resulting from a call to `summary.gnlFit`.
`digits`	The number of significant digits to use when printing.
`...`	Further arguments passed to or from other methods.

summary.gnlFit calculates standard errors for the estimates of mu, sigma, alpha, beta and rho of the Generalised Normal Laplace distribution parameter vector param if the Hessian from the call to gnlFit is available.

If the Hessian is available, summary.gnlFit computes standard errors for the estimates of mu, sigma, alpha, beta and rho and adds them to object as object$sds. Otherwise, no calculations are performed and the composition of object is unaltered.

summary.gnlFit invisibly returns object with class changed to summary.gnlFit.

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

print.summary.gnlFit prints a summary in the same format as print.gnlFit 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.

gnlFit, summary.

## Continuing the  gnlFit() example:
param <- c(2, 2, 1, 1, 1)
dataVector <- rgnl(500, param = param)
fit <- gnlFit(dataVector, hessian = TRUE)
print(fit)
summary(fit)