/nonlinear_regression_operator

Fit non linear curves to a set of data points.

Primary LanguageR

Nonlinear regression operator

Description

The nonlinear_regression operator fits a non linear function to observed data.

Different models are available:

  • the Three-parameter log-logistic (also know as the 3PL nonlinear regression model)
  • the Four-parameter log-logistic
  • the Michaelis-Menten often used in enzyme kinetics
Usage
Input projection .
y-axis measurement value (e.g. response)
x-axis explanatory value (e.g. dose)
Output relations .
function.type Model to be fitted. Any of Three-parameter log-logistic, Four-parameter log-logistic or Michaelis-Menten.
n.predictions Number of predicted values to generate.
response.output Comma-separated list of percentages of maximal response to generate predicted values for (for example,Y50 will give you the EC50 value as X50, Y50 being hald the maximal response value).
Output relations .
parameters numeric, fitted parameters (depend on the fitted model)
x-pred predicted x-values
y-pred predicted y-values
Details

Here is a good introduction to non-linear regression.

See Nonlinear regression on Wikipedia.

See Also

lm_operator