R: Print (or summarise) the results of a starship estimation

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 `starship`.
`object` | An object of class `starship`.
`digits` | minimal number of significant digits, see `print.default`.
`...` | arguments passed to `print`

### Details

`summary` Gives the details of the `starship.adaptivegrid` and `optim` steps.

### Author(s)

Robert King, robert.king@newcastle.edu.au, https://tolstoy.newcastle.edu.au/~rking/

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://tolstoy.newcastle.edu.au/~rking/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)

[Package gld version 2.6.2 Index]