55. Bibliografia#
- AH19
Jim Albert and Jingchen Hu. Probability and Bayesian Modeling. Chapman and Hall/CRC, 2019.
- Bak16
Monya Baker. Reproducibility crisis? Nature, 533(26):353–366, 2016.
- Bor14
Emile Borel. Introduction Géométrique. G. Villars, New York, 1914.
- CGH+17
Bob Carpenter, Andrew Gelman, Matthew D Hoffman, Daniel Lee, Ben Goodrich, Michael Betancourt, Marcus Brubaker, Jiqiang Guo, Peter Li, and Allen Riddell. Stan: a probabilistic programming language. Journal of statistical software, 76(1):1–32, 2017.
- Cla21
Aubrey Clayton. Bernoulli's Fallacy: Statistical Illogic and the Crisis of Modern Science. Columbia University Press, 2021.
- Dow21
Allen B Downey. Think Bayes. " O'Reilly Media, Inc.", 2021.
- DKPR87
Simon Duane, Anthony D Kennedy, Brian J Pendleton, and Duncan Roweth. Hybrid monte carlo. Physics letters B, 195(2):216–222, 1987.
- GDLB+08
David R Gagnon, Susan Doron-LaMarca, Margret Bell, Timothy J O'Farrell, and Casey T Taft. Poisson regression for modeling count and frequency outcomes in trauma research. Journal of Traumatic Stress, 21(5):448–454, 2008.
- GLP+20
P. Gautret, J. C. Lagier, P. Parola, L. Meddeb, M. Mailhe, B. Doudier, and S. ... Honoré. Hydroxychloroquine and azithromycin as a treatment of covid-19: results of an open-label non-randomized clinical trial. International Journal of Antimicrobial Agents, 2020.
- Gel16
Andrew Gelman. Commentary on “crisis in science? or crisis in statistics! mixed messages in statistics with impact on science”. Journal of Statistical Research, 48-50(1):11–12, 2016.
- GHV20
Andrew Gelman, Jennifer Hill, and Aki Vehtari. Regression and other stories. Cambridge University Press, 2020.
- GG84
Stuart Geman and Donald Geman. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on pattern analysis and machine intelligence, 6:721–741, 1984.
- Gut21
John V Guttag. Introduction to computation and programming using Python. Mit Press, 2021.
- Has70
W. Keith Hastings. Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 57(1):97–109, 1970.
- HMRW14
Rink Hoekstra, Richard D Morey, Jeffrey N Rouder, and Eric-Jan Wagenmakers. Robust misinterpretation of confidence intervals. Psychonomic Bulletin & Review, 21(5):1157–1164, 2014.
- HG+14
Matthew D Hoffman, Andrew Gelman, and others. The no-u-turn sampler: adaptively setting path lengths in hamiltonian monte carlo. Journal of Machine Learning Research, 15(1):1593–1623, 2014.
- HWD+20
O. J. Hulme, E. J. Wagenmakers, P. Damkier, C. F. Madelung, H. R. Siebner, J. Helweg-Larsen, and K. H. ... Madsen. Reply to gautret et al. 2020: a bayesian reanalysis of the effects of hydroxychloroquine and azithromycin on viral carriage in patients with covid-19. medRxiv, 2020.
- Ioa05
John PA Ioannidis. Why most published research findings are false. PLoS medicine, 2(8):e124, 2005.
- JOD22
Alicia A. Johnson, Miles Ott, and Mine Dogucu. Bayes Rules! An Introduction to Bayesian Modeling with R. CRC Press, 2022.
- Kru14
John Kruschke. Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan. Academic Press, 2014.
- LW14
Michael D Lee and Eric-Jan Wagenmakers. Bayesian cognitive modeling: A practical course. Cambridge university press, 2014.
- LG17
Eric Loken and Andrew Gelman. Measurement error and the replication crisis. Science, 355(6325):584–585, 2017.
- MKL22
Osvaldo A Martin, Ravin Kumar, and Junpeng Lao. Bayesian Modeling and Computation in Python. CRC Press, 2022.
- McE20
Richard McElreath. Statistical rethinking: A Bayesian course with examples in R and Stan. CRC Press, Boca Raton, Florida, 2nd edition edition, 2020.
- McK22
Wes McKinney. Python for Data Analysis. " O'Reilly Media, Inc.", 2022.
- MSS16
S. A. Mehr, L. A. Song, and E. S. Spelke. For 5-month-old infants, melodies are social. Psychological Science, 27(4):486–501, 2016.
- MRR+53
Nicholas Metropolis, Arianna W. Rosenbluth, Marshall N. Rosenbluth, Augusta H. Teller, and Edward Teller. Equation of state calculations by fast computing machines. The Journal of Chemical Physics, 21(6):1087–1092, 1953.
- Mil63
Stanley Milgram. Behavioral study of obedience. The Journal of Abnormal and Social Psychology, 67(4):371–378, 1963.
- Nuz14
Regina Nuzzo. Statistical errors. Nature, 506(7487):150–152, 2014.
- Per23
Jeffrey M Perkel. The sleight-of-hand trick that can simplify scientific computing. Nature, 617(7959):212–213, 2023.
- Sah13
Marshall Sahlins. Stone age economics. Routledge, 2013.
- Ste46
Stanley Smith Stevens. On the theory of scales of measurement. Science, 103(2684):677–680, 1946.
- Unp22
José Unpingco. Python for probability, statistics, and machine learning. Volume 1. Springer, 2022.
- vdSDK+21
Rens van de Schoot, Sarah Depaoli, Ruth King, Bianca Kramer, Kaspar Märtens, Mahlet G. Tadesse, Marina Vannucci, Andrew Gelman, Duco Veen, Joukje Willemsen, and Christopher Yau. Bayesian statistics and modelling. Nature Reviews Methods Primer, 1(1):1–26, 2021.
- WL16
Ronald L Wasserstein and Nicole A Lazar. The ASA's statement on p-values: context, process, and purpose. The American Statistician, 70(2):129–133, 2016.
- ZBR19
Ulrike Zetsche, Paul-Christian Buerkner, and Babette Renneberg. Future expectations in clinical depression: biased or realistic? Journal of Abnormal Psychology, 128(7):678, 2019.