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Parameter Estimation in Large Dynamic Paired Comparison Experiments

Citations

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Cited by:

  1. Kovalchik, Stephanie, 2020. "Extension of the Elo rating system to margin of victory," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1329-1341.
  2. Diego Fernandez Slezak & Mariano Sigman & Guillermo A Cecchi, 2018. "An entropic barriers diffusion theory of decision-making in multiple alternative tasks," PLOS Computational Biology, Public Library of Science, vol. 14(3), pages 1-14, March.
  3. Kovalchik Stephanie Ann, 2016. "Searching for the GOAT of tennis win prediction," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 12(3), pages 127-138, September.
  4. Mitchell J. Lovett & Ron Shachar, 2011. "The Seeds of Negativity: Knowledge and Money," Marketing Science, INFORMS, vol. 30(3), pages 430-446, 05-06.
  5. Fagan Francois & Haugh Martin & Cooper Hal, 2019. "The advantage of lefties in one-on-one sports," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 15(1), pages 1-25, March.
  6. McHale, Ian & Morton, Alex, 2011. "A Bradley-Terry type model for forecasting tennis match results," International Journal of Forecasting, Elsevier, vol. 27(2), pages 619-630, April.
  7. Chao, Xiangrui & Kou, Gang & Li, Tie & Peng, Yi, 2018. "Jie Ke versus AlphaGo: A ranking approach using decision making method for large-scale data with incomplete information," European Journal of Operational Research, Elsevier, vol. 265(1), pages 239-247.
  8. P. Gorgi & Siem Jan (S.J.) Koopman & R. Lit, 2018. "The analysis and forecasting of ATP tennis matches using a high-dimensional dynamic model," Tinbergen Institute Discussion Papers 18-009/III, Tinbergen Institute.
  9. Alexandra Grand & Regina Dittrich & Brian Francis, 2015. "Markov models of dependence in longitudinal paired comparisons: an application to course design," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(2), pages 237-257, April.
  10. Silvia Montagna & Vanessa Orani & Raffaele Argiento, 2021. "Bayesian isotonic logistic regression via constrained splines: an application to estimating the serve advantage in professional tennis," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 573-604, June.
  11. Lasek, Jan & Gagolewski, Marek, 2021. "Interpretable sports team rating models based on the gradient descent algorithm," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1061-1071.
  12. Murray Thomas A., 2017. "Ranking ultimate teams using a Bayesian score-augmented win-loss model," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 13(2), pages 63-78, June.
  13. Rose D. Baker & Ian G. McHale, 2015. "Time varying ratings in association football: the all-time greatest team is.," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(2), pages 481-492, February.
  14. Baker, Rose D. & McHale, Ian G., 2014. "A dynamic paired comparisons model: Who is the greatest tennis player?," European Journal of Operational Research, Elsevier, vol. 236(2), pages 677-684.
  15. Scott, Steven L., 2004. "A Bayesian paradigm for designing intrusion detection systems," Computational Statistics & Data Analysis, Elsevier, vol. 45(1), pages 69-83, February.
  16. Yuval Salant & Jörg L. Spenkuch, 2021. "Complexity and Choice," CESifo Working Paper Series 9239, CESifo.
  17. Blaž Krese & Erik Štrumbelj, 2021. "A Bayesian approach to time-varying latent strengths in pairwise comparisons," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-17, May.
  18. Szczecinski Leszek, 2022. "G-Elo: generalization of the Elo algorithm by modeling the discretized margin of victory," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 18(1), pages 1-14, March.
  19. Collingwood, James A.P. & Wright, Michael & Brooks, Roger J, 2022. "Evaluating the effectiveness of different player rating systems in predicting the results of professional snooker matches," European Journal of Operational Research, Elsevier, vol. 296(3), pages 1025-1035.
  20. Cristiano Varin & Manuela Cattelan & David Firth, 2016. "Statistical modelling of citation exchange between statistics journals," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(1), pages 1-63, January.
  21. McHale, Ian & Morton, Alex, 2011. "A Bradley-Terry type model for forecasting tennis match results," International Journal of Forecasting, Elsevier, vol. 27(2), pages 619-630.
  22. Devlin Stephen & Treloar Thomas & Creagar Molly & Cassels Samuel, 2021. "An iterative Markov rating method," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 17(2), pages 117-127, June.
  23. Owen G. Ward & Jing Wu & Tian Zheng & Anna L. Smith & James P. Curley, 2022. "Network Hawkes process models for exploring latent hierarchy in social animal interactions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1402-1426, November.
  24. Song, Kai & Shi, Jian, 2020. "A gamma process based in-play prediction model for National Basketball Association games," European Journal of Operational Research, Elsevier, vol. 283(2), pages 706-713.
  25. Irons David J. & Buckley Stephen & Paulden Tim, 2014. "Developing an improved tennis ranking system," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 10(2), pages 109-118, June.
  26. Chan Victor, 2011. "Prediction Accuracy of Linear Models for Paired Comparisons in Sports," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(3), pages 1-35, July.
  27. Santos-Fernandez Edgar & Wu Paul & Mengersen Kerrie L., 2019. "Bayesian statistics meets sports: a comprehensive review," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 15(4), pages 289-312, December.
  28. Beaudoin, David & Swartz, Tim, 2018. "A computationally intensive ranking system for paired comparison data," Operations Research Perspectives, Elsevier, vol. 5(C), pages 105-112.
  29. Mark Glickman, 2001. "Dynamic paired comparison models with stochastic variances," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(6), pages 673-689.
  30. Newton Paul K & Aslam Kamran, 2009. "Monte Carlo Tennis: A Stochastic Markov Chain Model," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(3), pages 1-44, July.
  31. Angelini, Giovanni & Candila, Vincenzo & De Angelis, Luca, 2022. "Weighted Elo rating for tennis match predictions," European Journal of Operational Research, Elsevier, vol. 297(1), pages 120-132.
  32. Hua, Hsuan-Fu & Chang, Ching-Ju & Lin, Tse-Ching & Weng, Ruby Chiu-Hsing, 2024. "Rating players by Laplace’s approximation and dynamic modeling," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1152-1165.
  33. Stokes Tyrel & Bagga Gurashish & Kroetch Kimberly & Kumagai Brendan & Welsh Liam, 2024. "A generative approach to frame-level multi-competitor races," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 20(4), pages 365-383.
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