Bibliografía

Bibliografía principal

Johnson, Ott, y Dogucu (2022) McElreath (2020) Gelman y Hill (2006) Kruschke (2014) Reich y Ghosh (2019)

Gelman, Andrew, y Jennifer Hill. 2006. Data Analysis Using Regression and Multilevel-Hierarchical Models. 1st edition. Cambridge University Press.

Johnson, Alicia A., Miles Q. Ott, y Mine Dogucu. 2022. Bayes Rules! An Introduction to Bayesian Modeling. 1st edition. Chapman; Hall/CRC. https://www.bayesrulesbook.com/.

Kruschke, John. 2014. Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan. 2nd edition. Academic Press.

McElreath, Richard. 2020. Statistical Rethinking: A Bayesian Course with Examples in R and Stan. 2nd edition. Chapman; Hall/CRC.

Reich, Brian J., y Sujit K. Ghosh. 2019. Bayesian Statistical Methods. 1st edition. Chapman; Hall/CRC.

Bibliografía complementaria

Gelman et al. (2013), Gelman, Hill, y Vehtari (2021), Downey (2021), Lee y Wagenmakers (2014), Davidson-Pilon (2015), Nicenboim, Schad, y Vasishth (2022), Barr (2021), Carlin y Louis (2008), Hoff (2009), MacKay (2003), Lambert (2018), Murphy (2022), Murphy (2023), Bishop (2006), Martin, Kumar, y Lao (2021), Theoridis (2020), Clyde et al. (2022), Ma, Kording, y Goldreich (2022)

Barr, Dale J. 2021. Learning statistical models through simulation in R: An interactive textbook. 1st edition. https://psyteachr.github.io/stat-models-v1/.

Bishop, Christopher M. 2006. Pattern Recognition and Machine Learning. 1st edition. Springer.

Carlin, Bradley P., y Thomas A. Louis. 2008. Bayesian Methods for Data Analysis. 3rd edition. Chapman; Hall/CRC.

Clyde, Merlise, Mine Çetinkaya-Rundel, Colin Rundel, David Banks, Christine Chai, y Lizzy Huang. 2022. An Introduction to Bayesian Thinking. 1st edition. https://statswithr.github.io/book/.

Davidson-Pilon, Cameron. 2015. Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference. 1st edition. Addison-Wesley Data; Analytics Series.

Downey, Allen B. 2021. Think Bayes: Bayesian Statistics in Python. 2nd edition. O’Reilly Media. http://allendowney.github.io/ThinkBayes2/.

Gelman, Andrew, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, y Donald B. Rubin. 2013. Bayesian Data Analysis. 3rd edition. Chapman; Hall/CRC.

Gelman, Andrew, Jennifer Hill, y Aki Vehtari. 2021. Regression and Other Stories. 1st edition. Cambridge University Press. https://users.aalto.fi/~ave/ROS.pdf.

Hoff, Peter D. 2009. A First Course in Bayesian Statistical Methods. 1st edition. Springer.

Lambert, Ben. 2018. A Student’s Guide to Bayesian Statistics. 1st edition. SAGE Publications Ltd.

Lee, Michael D., y Eric-Jan Wagenmakers. 2014. Bayesian Cognitive Modeling: A Practical Course. 1st edition. Cambridge University Press.

Ma, Wei Ji, Konrad P. Kording, y Daniel Goldreich. 2022. Bayesian Models of Perception and Action: An Introduction. 3rd edition. http://www.cns.nyu.edu/malab/bayesianbook.html.

MacKay, David J. C. 2003. Information Theory, Inference and Learning Algorithms. 1st edition. Cambridge University Press.

Martin, Osvaldo A., Ravin Kumar, y Junpeng Lao. 2021. Bayesian Modeling and Computation in Python. 1st edition. Chapman; Hall/CRC.

Murphy, Kevin P. 2022. Probabilistic Machine Learning: An Introduction. 1st edition. The MIT Press. https://probml.ai/.

Murphy, Kevin P. 2023. Probabilistic Machine Learning: Advanced Topics. 1st edition. The MIT Press. https://probml.ai/.

Nicenboim, Bruno, Daniel Schad, y Shravan Vasishth. 2022. An Introduction to Bayesian Data Analysis for Cognitive Science. https://vasishth.github.io/bayescogsci/book/.

Theoridis, Sergios. 2020. Machine Learning: A Bayesian and Optimization Perspective. 2nd edition. Academic Press.