References

Acemoglu, Daron, and Pascual Restrepo. 2018. “Artificial Intelligence, Automation and Work.” National Bureau of Economic Research.

Albert, Jim. 1993. “A Statistical Analysis of Hitting Streaks in Baseball: Comment.” Journal of the American Statistical Association 88 (424): 1184–88. https://www.jstor.org/stable/2291255.

Amazon. 2021. “The History of Amazon’s Forecasting Algorithm.” Amazon Science. https://www.amazon.science/latest-news/the-history-of-amazons-forecasting-algorithm.

Arnol’d, Vladimir I. 2006. “Forgotten and Neglected Theories of Poincaré.” Russian Mathematical Surveys 61 (1): 1.

Baylor, Denis, Eric Breck, Heng-Tze Cheng, Noah Fiedel, Chuan Yu Foo, Zakaria Haque, Salem Haykal, et al. 2017. “Tfx: A Tensorflow-Based Production-Scale Machine Learning Platform.” In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1387–95. ACM.

Benoit, Dries F., and Dirk Van den Poel. 2012. “Binary Quantile Regression: A Bayesian Approach Based on the Asymmetric Laplace Distribution.” Journal of Applied Econometrics 27 (7): 1174–88.

Berge, Travis, Nitish Sinha, and Michael Smolyansky. 2016. “Which Market Indicators Best Forecast Recessions?” FEDS Notes, August.

Bojarski, Mariusz, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D Jackel, et al. 2016. “End to End Learning for Self-Driving Cars.” arXiv Preprint arXiv:1604.07316. https://arxiv.org/abs/1604.07316.

Campagnoli, Patrizia, Sonia Petrone, and Giovanni Petris. 2009. Dynamic Linear Models with R. New York, NY: Springer.

Cootner, Paul H. 1967. The Random Character of Stock Market Prices. MIT press.

Davison, Anthony Christopher. 2003. Statistical Models. Vol. 11. Cambridge university press.

Eric Tassone, and Farzan Rohani. 2017. “Our Quest for Robust Time Series Forecasting at Scale.”

Frühwirth-Schnatter, Sylvia, and Rudolf Frühwirth. 2007. “Auxiliary Mixture Sampling with Applications to Logistic Models.” Computational Statistics & Data Analysis 51 (April): 3509–28.

———. 2010. “Data Augmentation and MCMC for Binary and Multinomial Logit Models.” In Statistical Modelling and Regression Structures: Festschrift in Honour of Ludwig Fahrmeir, 111–32.

Frühwirth-Schnatter, Sylvia, Rudolf Frühwirth, Leonhard Held, and Håvard Rue. 2008. “Improved Auxiliary Mixture Sampling for Hierarchical Models of Non-Gaussian Data.” Statistics and Computing 19 (4): 479.

Gramacy, Robert B., and Nicholas G. Polson. 2012. “Simulation-Based Regularized Logistic Regression.” arXiv. https://arxiv.org/abs/1005.3430.

Held, Leonhard, and Chris C. Holmes. 2006. “Bayesian Auxiliary Variable Models for Binary and Multinomial Regression.” Bayesian Analysis 1 (1): 145–68.

Hermann, Jeremy, and Mike Del Balso. 2017. “Meet Michelangelo: Uber’s Machine Learning Platform.”

Hyndman, Rob J., and George Athanasopoulos. 2021. Forecasting: Principles and Practice. 3rd ed. edition. Melbourne, Australia: Otexts.

indeed. 2018. “Jobs of the Future: Emerging Trends in Artificial Intelligence.”

Januschowski, Tim, Yuyang Wang, Kari Torkkola, Timo Erkkilä, Hilaf Hasson, and Jan Gasthaus. 2022. “Forecasting with Trees.” International Journal of Forecasting, Special Issue: M5 competition, 38 (4): 1473–81.

kaggle. 2020. “M5 Forecasting - Accuracy.” https://kaggle.com/competitions/m5-forecasting-accuracy.

Keynes, John Maynard. 1921. A Treatise on Probability. Macmillan.

Kolmogoroff, Andrei. 1931. “Über Die Analytischen Methoden in Der Wahrscheinlichkeitsrechnung.” Mathematische Annalen 104 (1): 415–58.

Kolmogorov, A. N. 1938. “On the Analytic Methods of Probability Theory.” Uspekhi Mat. Nauk, no. 5: 5–41.

Kolmogorov, AN. 1942. “Definition of Center of Dispersion and Measure of Accuracy from a Finite Number of Observations (in Russian).” Izv. Akad. Nauk SSSR Ser. Mat. 6: 3–32.

Kreps, David. 1988. Notes On The Theory Of Choice. Boulder: Westview Press.

Logunov, A. A. 2004. “Henri Poincare and Relativity Theory.” https://arxiv.org/abs/physics/0408077.

Maharaj, Shiva, Nick Polson, and Vadim Sokolov. 2023. “Kramnik Vs Nakamura or Bayes Vs p-Value.” {{SSRN Scholarly Paper}}. Rochester, NY.

Mehrasa, Nazanin, Yatao Zhong, Frederick Tung, Luke Bornn, and Greg Mori. 2017. “Learning Person Trajectory Representations for Team Activity Analysis.” arXiv Preprint arXiv:1706.00893. https://arxiv.org/abs/1706.00893.

Petris, Giovanni. 2010. “An R Package for Dynamic Linear Models.” Journal of Statistical Software 36 (October): 1–16.

Poincaré, Henri. 1898. “La Mesure Du Temps.” Revue de métaphysique Et de Morale 6 (1): 1–13.

Polson, Nicholas, and Steven Scott. 2011. “Data Augmentation for Support Vector Machines.” Bayesian Analysis 6 (March).

Poplin, Ryan, Avinash V Varadarajan, Katy Blumer, Yun Liu, Michael V McConnell, Greg S Corrado, Lily Peng, and Dale R Webster. 2018. “Prediction of Cardiovascular Risk Factors from Retinal Fundus Photographs via Deep Learning.” Nature Biomedical Engineering 2 (3): 158.

Rubin, Hal S. Stern, John B. Carlin. 2015. Bayesian Data Analysis. 3rd ed. New York: Chapman and Hall/CRC.

Scott, Steven L. 2015. “Multi-Armed Bandit Experiments in the Online Service Economy.” Applied Stochastic Models in Business and Industry 31 (1): 37–45.

Scott, Steven L. 2022. “BoomSpikeSlab: MCMC for Spike and Slab Regression.”

Scott, Steven L., and Hal R. Varian. 2015. “Bayesian Variable Selection for Nowcasting Economic Time Series.” In Economic Analysis of the Digital Economy, 119–35. University of Chicago Press.

Scott, Steven, and Hal Varian. 2014. “Predicting the Present with Bayesian Structural Time Series.” Int. J. Of Mathematical Modelling and Numerical Optimisation 5 (January): 4–23.

Sean J. Taylor, and Ben Letham. 2017. “Prophet: Forecasting at Scale - Meta Research.” Meta Research. https://research.facebook.com/blog/2017/2/prophet-forecasting-at-scale/.

Shen, Changyu, Enrico G Ferro, Huiping Xu, Daniel B Kramer, Rushad Patell, and Dhruv S Kazi. 2021. “Underperformance of Contemporary Phase III Oncology Trials and Strategies for Improvement.” Journal of the National Comprehensive Cancer Network 19 (9): 1072–78.

Shiryayev, A. N. 1992. “On Analytical Methods in Probability Theory.” In Selected Works of a. N. Kolmogorov: Volume II Probability Theory and Mathematical Statistics, edited by A. N. Shiryayev, 62–108. Dordrecht: Springer Netherlands.

Silver, David, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, et al. 2017. “Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm.” arXiv. https://arxiv.org/abs/1712.01815.

Simpson, Edward. 2010. “Edward Simpson: Bayes at Bletchley Park.” Significance 7 (2): 76–80.

Spiegelhalter, David, and Yin-Lam Ng. 2009. “One Match to Go!” Significance 6 (4): 151–53.

Stern, H, Adam Sugano, J Albert, and R Koning. 2007. “Inference about Batter-Pitcher Matchups in Baseball from Small Samples.” Statistical Thinking in Sports, 153–65.

Sun, Duxin, Wei Gao, Hongxiang Hu, and Simon Zhou. 2022. “Why 90% of Clinical Drug Development Fails and How to Improve It?” Acta Pharmaceutica Sinica B 12 (7): 3049–62.

Taleb, Nassim Nicholas. 2007. The Black Swan: The Impact of the Highly Improbable. Annotated edition. New York. N.Y: Random House.

Tesauro, Gerald. 1995. “Temporal Difference Learning and TD-Gammon.” Communications of the ACM 38 (3): 58–68.

Wojna, Zbigniew, Alex Gorban, Dar-Shyang Lee, Kevin Murphy, Qian Yu, Yeqing Li, and Julian Ibarz. 2017. “Attention-Based Extraction of Structured Information from Street View Imagery.” arXiv Preprint arXiv:1704.03549. https://arxiv.org/abs/1704.03549.