Overview

The purpose of this package is to provide an implementation of True and Error Theory (TET; Birnbaum, & Quispe-Torreblanca, 2018) in the Julia programming language. TET provides a mathematical framework for distinguishing between true preferences and errors in option evaluation and selection. For example, a person who selects risky option $\mathcal{R}$ over safe option $\mathcal{S}$ may truely prefer $\mathcal{R}$, or may truely prefer $\mathcal{S}$, but committed an error during the evaluation process. For more details, see the section titled Model Overview.

Key Features

One of the most valuable benefits of TrueAndErrorModels.jl is its seemless integration with the Julia ecosystem. Key examples include

• Distributions.jl: a common interface for probability distributions, including probability density functions, cumulative distribution functions, means etc.
• Turing.jl: an ecosystem for Bayesian parameter estimation, maximum likelihood estimation, variational inference and more.
• Pigeons.jl: a package for Bayes factors and Bayesian parameter estimation, specializing with intractible, multimodal posterior distributions. Pigeons.jl is compatible with Turing.jl.

References

Birnbaum, M. H., & Quispe-Torreblanca, E. G. (2018). TEMAP2. R: True and error model analysis program in R. Judgment and Decision Making, 13(5), 428-440.

Lee, M. D. (2018). Bayesian methods for analyzing true-and-error models. Judgment and Decision Making, 13(6), 622-635.