Fits a model to provided data using the Differential Evolution optimization algorithm. It optimizes the model parameters to minimize the sum of squared errors (SSE) between the model's predictions and human accuracy data.
Usage
xsl_fit(
model,
data,
lower,
upper,
by_data = FALSE,
control = xslControl(),
deoptim_control = DEoptim::DEoptim.control(reltol = 0.001, NP = 100, itermax = 100)
)Arguments
- model
An object of class xslMod.
- data
An object (or list of objects) of class xslData.
- lower
Numeric vector of lower bounds for the model's parameters.
- upper
Numeric vector of upper bounds for the model's parameters.
- by_data
Logical indicating whether to fit to each entry in data separately.
- control
Control parameters passed to
xsl_run().- deoptim_control
Control parameters passed to
DEoptim().