# Maximising responses with error

### Description

Construct a `MaxResponse`

object.

### Usage

1 2 |

### Arguments

`formula` |
an object of class |

`data` |
(optional) data frame. |

`parameters` |
an (optional) named list with (starting) values of the parameters. The model has one parameter (beta), which sets the error rate (see details). If no values are supplied, defaults are used. |

`ntimes` |
an optional vector with, for each repetition in the data, the total number of trials. |

`replicate` |
logical to indicate whether model parameters are identical for each replication in ntimes. |

`fixed` |
a logical vector indicating whether model parameters are fixed or free |

`parStruct` |
a ParStruct object. If supplied, the fixed argument above will be ignored |

`subset` |
(optional) subset. |

### Details

The `MaxResponse`

function sets up a
`MaxResponse`

model. This model predicts categorical
responses R = 1,...,k on the basis of predictors x[j], j = 1,...,k, as
P(R=j) = 1 - exp(beta)/(1+exp(beta))
if j = arg max x[j]
and
P(R=j) = exp(beta)/(1+exp(beta))
otherwise.

### Value

A (fitted) object of class `MaxResponse`

.