mixture: Fitting binary mixture models

In MaximeBSanofi/drc2:

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).

MaximeBSanofi/drc2 documentation built on Feb. 22, 2022, 12:02 a.m.