R: Fitting binary mixture models

mixture {drc} | R Documentation

## Fitting binary mixture models

### Description

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

### Usage

      mixture(object, model = c("CA", "Hewlett", "Voelund"), start, startm, control = drmc())

### Arguments

`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.

### Details

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.

### Value

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

### Author(s)

Christian Ritz

### References

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

### See Also

The examples in `acidiq` (the Hewlett model), `glymet` (dose/concentration addition) and `mecter` (the Voelund model).

[Package drc version 3.0-1 Index]