xsl_fit: Fit XSL model using differential evolution

In XSLmodels: Run and Optimize Cross-Situational Word Learning Models

Fit XSL model using differential evolution

Description

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().

Value

An object of class DEoptim representing the fitting result, which includes the best set of parameters found and the corresponding SSE value.

XSLmodels documentation built on Oct. 18, 2026, 5:08 p.m.