Description Usage Arguments Details Value

The function `mblogit`

fits multinomial logit models for categorical
and multinomial count responses with fixed alternatives, where the logits are
relative to a baseline category.

1 2 3 |

`formula` |
the model formula. The response must be a factor or a matrix of counts. |

`data` |
an optional data frame, list or environment (or object
coercible by |

`subset` |
an optional vector specifying a subset of observations to be used in the fitting process. |

`weights` |
an optional vector of weights to be used in the fitting
process. Should be |

`na.action` |
a function which indicates what should happen
when the data contain |

`model` |
a logical value indicating whether |

`x,y` |
logical values indicating whether the response vector and model matrix used in the fitting process should be returned as components of the returned value. |

`contrasts` |
an optional list. See the |

`control` |
a list of parameters for the fitting process.
See |

`...` |
arguments to be passed to |

The function `mblogit`

internally rearranges the data
into a 'long' format and uses `mclogit.fit`

to compute
estimates. Nevertheless, the 'user data' is unaffected.

`mblogit`

returns an object of class "mblogit", which has almost the
same structure as an object of class "glm". The difference are
the components `coefficients`

, `residuals`

, `fitted.values`

,
`linear.predictors`

, and `y`

, which are matrices with
number of columns equal to the number of response categories minus one.

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.