# A interface function to use rpart() function within GAMLSS

### Description

The tr() function is a additive function to be used for GAMLSS models. It is an interface for the `rpart()`

function of package `rpart`

. The function tr() allows the user to use regression trees within gamlss. The great advantage of course comes from the fact GAMLSS models provide a variety of distributions and diagnostics. Note that the function gamlss.tr is not used by the user but it needed for the backfitting.

### Usage

1 2 |

### Arguments

`formula` |
A formula containing the expolanatory variables i.e. |

`method` |
only method "rpart" is supported at the moment |

`control` |
control here is equivalent to |

`x` |
object passing informatio to the function |

`y` |
the iterative y variable |

`w` |
the iterative weights |

`xeval` |
whether prediction or not is used |

`...` |
additional arguments |

### Details

Note that, the gamlss fit maybe would not coverged. Also occasianly the `gd.tol`

argument in `gamlss`

has to be increased. The

### Value

Note that `tr`

itself does no smoothing; it simply sets things up for the function `gamlss()`

which in turn uses the function `additive.fit()`

for backfitting which in turn uses `gamlss.tr()`

The result is a `rpart`

object.

### Author(s)

Mikis Stasinopoulos mikis.stasinopoulos@gamlss.org, Bob Rigby based on work of Therneau and Atkison (2015)

### References

Ripley, B. D. (1996) Pattern Recognition and Neural Networks. Cambridge.

Stasinopoulos D. M., Rigby R.A. and Akantziliotou C. (2006) Instructions on how to use the GAMLSS package in R. Accompanying documentation in the current GAMLSS help files, (see also http://www.gamlss.org/).

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.

Therneau T. M., Atkinson E. J. (2015) An Introduction to Recursive Partitioning Using the RPART Routines. Vignette in package rpart.

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

### See Also

See Also as `nn`

### Examples

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ```
data(rent)
#--- fitting gamlss+tree Nornal
library(rpart)
data(rent)
rg1 <- gamlss(R ~ tr(~A+Fl), data=rent, family=NO)
plot(rg1)
plot(getSmo(rg1))
text(getSmo(rg1))
## Not run:
# fitting Gamma errors
rg2 <- gamlss(R ~ tr(~A+Fl), data=rent, family=GA)
plot(rg2)
plot(getSmo(rg2))
text(getSmo(rg2))
#--- fitting also model in the variance
rg3 <- gamlss(R ~ tr(~A+Fl), sigma.fo=~tr(~Fl+A), data=rent,
family=GA, gd.tol=100, c.crit=0.1)
plot(rg3)
plot(getSmo(rg3))
text(getSmo(rg3))
plot(getSmo(rg3, what="sigma"))
text(getSmo(rg3, what="sigma"))
## End(Not run)
``` |