'mixture' fits a concentration addition, Hewlett or Voelund model to data from binary mixture toxicity experiments.

1 |

`object` |
object of class 'drc' corresponding to the model with freely varying EC50 values. |

`model` |
character string. It can be "CA", "Hewlett" or "Voelund". |

`start` |
optional numeric vector supplying starting values for all parameters in the mixture model. |

`startm` |
optional numeric vector supplying the lambda parameter in the Hewlett model or the eta parameters (two parameters) in the Voelund model. |

`control` |
list of arguments controlling constrained optimisation (zero as boundary), maximum number of iteration in the optimisation, relative tolerance in the optimisation, warnings issued during the optimisation. |

The function is a wrapper to `drm`

, implementing the models described in Soerensen et al. (2007).
See the paper for a discussion of the merits of the different models.

Currently only the log-logistic models are available. Application of Box-Cox transformation is not yet available.

An object of class 'drc' with a few additional components.

Christian Ritz

Ritz, C. and Streibig, J. C. (2014)
From additivity to synergism - A modelling perspective
*Synergy*, **1**, 22–29.

The examples in `acidiq`

(the Hewlett model), `glymet`

(dose/concentration addition)
and `mecter`

(the Voelund model).

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.