R: Fits Different Parametric 'gamlss.family' distributions to...

fitDist {gamlss} | R Documentation

## Fits Different Parametric `gamlss.family` distributions to data

### Description

This function is using the function `gamlssML()` to fit all relevant parametric `gamlss.family` distributions to a data vector. The final model is the one which is selected by the generalised Akaike information criterion with penalty `k`.

### Usage

    fitDist(y, k = 2,
          type = c("realAll", "realline", "realplus", "real0to1", "counts", "binom"),
          try.gamlss = FALSE, extra = NULL, data = NULL, ...)

### Arguments

`y` | the data vector
`k` | the penalty for the GAIC with default values `k=2` the standard AIC
`type` | the type of distribution to be tried see details
`try.gamlss` | if `gamlssML()` failed whether should try `gamlss` instead. This will slow up things for big data.
`extra` | whether extra distribution should be tried which are not in the `type` list
`data` | the data frame where `y` ca be found
`...` | for extra arguments to be passed to gamlssML() to gamlss()

### Details

The following are the different `type` argument:

- `realAll` all the `gamlss.family` continuous distributions defined on the real line, i.e. `realline` plus `realplus`

- `realline`the `gamlss.family` continuous distributions : "GU", "RG" ,"LO", "NET", "TF", "PE", "SN1", "SN2", "SHASH", "EGB2", "JSU", "SEP1", "SEP2", "SEP3", "SEP4","ST1", "ST2", "ST3", "ST4", "ST5", "GT"

- `realplus` the `gamlss.family` continuous distributions in the positive leal line: "EXP","GA","IG","LNO", "WEI3", "BCCGo", "exGAUS", "GG", "GIG", "BCTo", "BCPEo"

- `real0to1`the `gamlss.family` continuous distributions from 0 to 1: "BE", "BEINF", "BEINF0", "BEINF1", "BEOI", "BEZI", "GB1"

- `counts`the `gamlss.family` distributions for counts: "PO", "LG", "NBI", "NBII", "PIG", "DEL", "SI", "ZIP", "ZAP", "ZALG", "ZANBI", "ZIP2", "ZIPIG"

- `binom`the `gamlss.family` distributions for binomial type data :"BI", "BB", "ZIBI", "ZIBB", "ZABI", "ZABB"

### Value

A `gamlssML` object with two extra components:

`fits` | an ordered list according to the GAIC of the fitted distribution
`failed` | the distributions where the `gamlssML)()` (or `gamlss()`) fits have failed

### Author(s)

Mikis Stasinopoulos mikis.stasinopoulos@gamlss.org, Bob Rigby, Vlasis Voudouris v.voiudouris@londonmet.ac.uk and Majid Djennad m.djennad.londonmet.ac.uk

### References

Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion), Appl. Statist., 54, part 3, pp 507-554.

Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, Vol. 23, Issue 7, Dec 2007, http://www.jstatsoft.org/v23/i07.

Stasinopoulos D. M., Rigby R.A., Heller G., Voudouris V., and De Bastiani F., (2017) Flexible Regression and Smoothing: Using GAMLSS in R, Chapman and Hall/CRC.

(see also http://www.gamlss.org/).

### See Also

`gamlss`,`gamlssML`

### Examples

    y <- rt(100, df=1)
    m1<-fitDist(y, type="realline")
    m1$fits
    m1$failed
    # an example of using  extra
    ## Not run:
    library(gamlss.tr)
    data(tensile)
    gen.trun(par=1,family="GA", type="right")
    gen.trun(par=1,"LOGNO", type="right")
    gen.trun(par=c(0,1),"TF", type="both")
    ma<-fitDist(str, type="real0to1", extra=c("GAtr", "LOGNOtr", "TFtr"), data=tensile)

    ## End(Not run)

[Package gamlss version 5.0-2 Index]