relativeLikelihood: Calculate relative likelihood of models based on information...

In thartbm/SMCL: Utilities for common tasks in the SensoriMotor Control Lab.

Calculate relative likelihood of models based on information criteria

Description

This function is part of a set of functions to fit and evaluate the two-rate model of motor learning.

Usage

relativeLikelihood(crit)

Arguments

crit	a numeric vector with the same informations criterion, for several models (fit on the same data).

Details

This function returns the relative likelihood of a series of models based on their scores on an information criterion (e.g. AIC or BIC). The best model will have a relative likelihood of 1, and models that have relative likelihoods between 1 and 0.05 are also good, while those below 0.05 can be considered worse than the best model.

Value

Returns the relative likelihoods of the models

Examples

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thartbm/SMCL documentation built on Oct. 23, 2022, 5:17 a.m.