gld: plot.starship – R documentation

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gld

plot.starship

Plots to compare a fitted generalised lambda distribution to data

Description

Plots to compare a Generalised Lambda Distribution fitted via the starship to data

Usage

## S3 method for class 'starship'
plot(x, data, ask = NULL, one.page = FALSE, 
    breaks = "Sturges", plot.title = "default",...)

Arguments

`x`	An object of class `starship`.
`data`	Data to which the gld was fitted. Leave this as NULL if the return.data argument was TRUE in the `starship` call that created x.
`ask`	Ask for user input before next plot. The default of NULL changes to TRUE if one.page is FALSE and `plot` is called interactively, otherwise it changes to FALSE this is then passed to `par(ask)`. Does not permanently change this setting. The argument is ignored if `one.page` is TRUE
`one.page`	If TRUE, put the two plots on one page using `par(mfrow=c(2,1))`. Does not permanently change this setting.
`breaks`	Control the number of histogram bins — passed to `hist`.
`plot.title`	Main title for histogram and QQ — passed to `hist(main=)` and `qqgl(main=)`. If you set this to `"default"`, it will include the fitting method and gld type, for example “Starship fit of FMKL type GLD”.
`...`	arguments passed to `plot` AND `hist`

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/

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

https://tolstoy.newcastle.edu.au/~rking/gld/

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),return.data=TRUE)
plot(starship.result)

gld

Estimation and Use of the Generalised (Tukey) Lambda Distribution

v2.6.2

GPL (>= 2)

Authors

Robert King <Robert.King@newcastle.edu.au>, Benjamin Dean <Benjamin.Dean@uon.edu.au>, Sigbert Klinke, Paul van Staden

Initial release

2020-01-07