fit_stochastic_model: Fit Stochastic Model to Conditions Using Differential...

In kachergis/XSLmodels: Run and optimize cross-situational word learning models

Fit Stochastic Model to Conditions Using Differential Evolution

Description

This function fits a stochastic model to provided conditions using the Differential Evolution optimization algorithm. It aims to optimize the model parameters to minimize the sum of squared errors (SSE) between the model's predictions and human accuracy data.

Usage

fit_stochastic_model(model_name, conds, lower, upper)

Arguments

model_name	A string specifying the name of the stochastic model to be fitted.
conds	A list representing the conditions under which the model is fit. This typically includes training data and expected outcomes.
lower	Numeric vector of lower bounds for the model's parameters.
upper	Numeric vector of upper bounds for the model's parameters.

Value

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

kachergis/XSLmodels documentation built on Feb. 25, 2024, 10:43 p.m.