# A fitted Mixture Model Detection Function Object

### Description

The fitted mixture model detection function object
returned by `fitmix`

. Knowledge of most of
this is not useful. Use `link{summary.ds.mixture}`

for result summaries.

### Details

A `ds.mixture`

object has the following
elements:

distance | Vector of distances used in the analysis. |

likelihood | Value of the log-likelihood at the maxima. |

pars | Parmeter
estimates. See `mmds.pars` for more
information. |

mix.terms | Number of mixture terms fit. |

width | Truncation distance used. |

z |
List containing the matrix of covariates used. Output
from `model.matrix` . |

zdim | Number of
columns of `z` . See `mmds.pars` for more
information. |

hessian | Hessian matrix at the maxima. |

pt | Logical indicating whether the data were from a point transect survey. |

data | Data frame after truncation. |

ftype | Type of detection function. |

ctrl.options | Options passed to
`optim` . |

showit | Debug level. |

opt.method | Optimisation method used. |

usegrad | Were analytic gradients used? |

model.formula | Model formula. |

mu | Per-observation effective trip width/effective area of detection. |

pa.vec | Vector of per-observation detectabilities. |

N | Estimate of N in the covered area (Horvitz-Thompson). |

pa | Average detectability. |

pars.se | Standard errors of the parameters. |

N.se | Standard error of the Horvitz-Thompson estimate of the abundance. |

pa.se | Standard error of the average detectability. |

aic | AIC of the fitted model. |

cvm | Cramer-von Mises GoF
test results. List containing: `p` , the p-value and
`W` , the test statistic. |

ks |
Kolmogorov-Smirnov test results. List containing:
`p` , the p-value and `Dn` , the test statistic.
See `mmds.gof` for more information. |

### Note

`ds.mixture`

objects can be passed to
`step.ds.mixture`

to select number of mixture
components based on AIC score.

### Author(s)

David L. Miller

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