print.starship {gld} | R Documentation |
Print (or summarise) the results of a starship estimation
Description
Print (or summarise) the results of a starship
estimation
of the parameters of the Generalised Lambda Distribution
Usage
## S3 method for class 'starship'
summary(object, ...)
## S3 method for class 'starship'
print(x, digits = max(3, getOption("digits") - 3), ...)
Arguments
x |
An object of class |
object |
An object of class |
digits |
minimal number of significant digits, see
|
... |
arguments passed to |
Details
summary
Gives the details of the starship.adaptivegrid
and optim
steps.
Author(s)
Robert King, robert.king.newcastle@gmail.com, https://github.com/newystats/
Darren Wraith
References
Freimer, M., Mudholkar, G. S., Kollia, G. & Lin, C. T. (1988), A study of the generalized tukey lambda family, Communications in Statistics - Theory and Methods 17, 3547–3567.
Ramberg, J. S. & Schmeiser, B. W. (1974), An approximate method for generating asymmetric random variables, Communications of the ACM 17, 78–82.
King, R.A.R. & MacGillivray, H. L. (1999), A starship method for
fitting the generalised \lambda
distributions,
Australian and New Zealand Journal of
Statistics 41, 353–374
Owen, D. B. (1988), The starship, Communications in Statistics - Computation and Simulation 17, 315–323.
https://github.com/newystats/gld/
See Also
starship
,
starship.adaptivegrid
,
starship.obj
Examples
data <- rgl(100,0,1,.2,.2)
starship.result <- starship(data,optim.method="Nelder-Mead",initgrid=list(lcvect=(0:4)/10,
ldvect=(0:4)/10))
print(starship.result)
summary(starship.result,estimation.details=TRUE)