* BESSIERE, P. et al. Bayesian Programming. 1st. ed. Boca Baton, FL: Chapman & Hall/CRC, 2014.
* BRAUN, W. J.; MURDOCH, D. J. A First Course in Statistical Programming With R. New York, NY: American Society for Quality, 2016.
* CARPENTER, B. et al. Stan: A Probabilistic Programming Language. Journal of Statistical Software, Columbia Univ., New York, NY (United States); Harvard Univ., Cambridge, MA (United States), v. 76, n. 1, 2017.
* COHEN, P. R. Empirical Methods for Artificial Intelligence. Cambridge, MA, USA:MIT Press, 1995.
* MATSUURA, K. Overview of Stan. In: Bayesian Statistical Modeling with Stan, R, and Python. Tokyo, Japan: Springer, 2023. p. 31–42.
* PFEFFER, A. Practical Probabilistic Programming. 1st. ed. Greenwich, CT, USA:Manning Publications Co., 2016.
* BAKER, F. B.; KIM, S.-H. The Basics of Item Response Theory Using R. 1st. ed. Switzerland: Springer, 2017.
* QIU, J. et al. Informetrics: Theory, Methods and Applications. 1. ed. New York, NY:Springer, 2017.