Description Usage Arguments Details Value Author(s) References See Also Examples

The set of function presented here is useful for fitting multinomial regression within gamlss.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ```
MN3(mu.link = "log", sigma.link = "log")
MN4(mu.link = "log", sigma.link = "log", nu.link = "log")
MN5(mu.link = "log", sigma.link = "log", nu.link = "log", tau.link = "log")
MULTIN(type = "3")
fittedMN(model)
dMN3(x, mu = 1, sigma = 1, log = FALSE)
dMN4(x, mu = 1, sigma = 1, nu = 1, log = FALSE)
dMN5(x, mu = 1, sigma = 1, nu = 1, tau = 1, log = FALSE)
pMN3(q, mu = 1, sigma = 1, lower.tail = TRUE, log.p = FALSE)
pMN4(q, mu = 1, sigma = 1, nu = 1, lower.tail = TRUE, log.p = FALSE)
pMN5(q, mu = 1, sigma = 1, nu = 1, tau = 1, lower.tail = TRUE, log.p = FALSE)
qMN3(p, mu = 1, sigma = 1, lower.tail = TRUE, log.p = FALSE)
qMN4(p, mu = 1, sigma = 1, nu = 1, lower.tail = TRUE, log.p = FALSE)
qMN5(p, mu = 1, sigma = 1, nu = 1, tau = 1, lower.tail = TRUE, log.p = FALSE)
rMN3(n, mu = 1, sigma = 1)
rMN4(n, mu = 1, sigma = 1, nu = 1)
rMN5(n, mu = 1, sigma = 1, nu = 1, tau = 1)
``` |

`mu.link` |
the link function for mu |

`sigma.link` |
the link function for sigma |

`nu.link` |
the link function for nu |

`tau.link` |
the link function for tau |

`x` |
the x variable |

`q` |
vector of quantiles |

`p` |
vector of probabilities |

`lower.tail` |
logical; if TRUE (default), probabilities are P[X <= x] otherwise, P[X > x]. |

`log.p` |
logical; if TRUE, probabilities p are given as log(p). |

`log` |
logical; if TRUE, probabilities p are given as log(p). |

`n` |
the number of observations |

`mu` |
the mu parameter |

`sigma` |
the sigma parameter |

`nu` |
the nu parameter |

`tau` |
the tau parameter |

`type` |
permitted values are 2 (Binomial), 3, 4, and 5 |

`model` |
a gamlss multinomial fitted model |

GAMLSS is in general not suitable for multinomial regression. Nevertheless multinomial regression can be fitted within GAMLSS if the response variable y has less than five categories. The function here provide the facilities to do so. The functions `MN3()`

, `MN4()`

and `MN5()`

fit multinomial responses with 3, 4 and 5 categories respectively.
The function `MULTIN()`

can be used instead of codeMN3(), `MN4()`

and `MN5()`

by specifying the number of levels of the response. Note that `MULTIN(2)`

will produce a binomial fit.

returns a `gamlss.family`

object which can be used to fit a binomial distribution in the `gamlss()`

function.

Mikis Stasinopoulos, Bob Rigby and Vlasios Voudouris

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.

Rigby, R. A., Stasinopoulos, D. M., Heller, G. Z., and De Bastiani, F. (2019) Distributions for modeling location, scale, and shape: Using GAMLSS in R, Chapman and Hall/CRC. An older version can be found in http://www.gamlss.com/.

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.

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