IDEAS home Printed from https://ideas.repec.org/r/bla/jorssc/v24y1975i2p193-202.html
   My bibliography  Save this item

The Analysis of Permutations

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Maryam Aghayerashti & Ehsan Bahrami Samani & Mojtaba Ganjali, 2023. "Bayesian Latent Variable Model of Mixed Correlated Rank and Beta-Binomial Responses with Missing Data for the International Statistical Literacy Project Poster Competition," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 210-250, May.
  2. Mukhtar Ali, 1998. "Probability models on horse-race outcomes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(2), pages 221-229.
  3. Pierpaolo D’Urso & Vincenzina Vitale, 2022. "A Kemeny Distance-Based Robust Fuzzy Clustering for Preference Data," Journal of Classification, Springer;The Classification Society, vol. 39(3), pages 600-647, November.
  4. 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.
  5. Naser Ansari-Pour & Yonglan Zheng & Toshio F. Yoshimatsu & Ayodele Sanni & Mustapha Ajani & Jean-Baptiste Reynier & Avraam Tapinos & Jason J. Pitt & Stefan Dentro & Anna Woodard & Padma Sheila Rajagop, 2021. "Whole-genome analysis of Nigerian patients with breast cancer reveals ethnic-driven somatic evolution and distinct genomic subtypes," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
  6. Tino Werner, 2022. "Elicitability of Instance and Object Ranking," Decision Analysis, INFORMS, vol. 19(2), pages 123-140, June.
  7. Heather L. Turner & Jacob Etten & David Firth & Ioannis Kosmidis, 2020. "Modelling rankings in R: the PlackettLuce package," Computational Statistics, Springer, vol. 35(3), pages 1027-1057, September.
  8. Dirk van Straaten & Vitalik Melnikov & Eyke Hüllermeier & Behnud Mir Djawadi & René Fahr, 2021. "Accounting for Heuristics in Reputation Systems: An Interdisciplinary Approach on Aggregation Processes," Working Papers Dissertations 72, Paderborn University, Faculty of Business Administration and Economics.
  9. Kumar Goutam & Vineet Goyal & Agathe Soret, 2019. "A Generalized Markov Chain Model to Capture Dynamic Preferences and Choice Overload," Papers 1911.06716, arXiv.org, revised Dec 2020.
  10. Mónica Hernández Alava & John Brazier & Donna Rowen & Aki Tsuchiya, 2013. "Common Scale Valuations across Different Preference-Based Measures," Medical Decision Making, , vol. 33(6), pages 839-852, August.
  11. Vivek F. Farias & Srikanth Jagabathula & Devavrat Shah, 2013. "A Nonparametric Approach to Modeling Choice with Limited Data," Management Science, INFORMS, vol. 59(2), pages 305-322, December.
  12. Jayanti Gupta & Paul Damien, 2002. "Conjugacy class prior distributions on metric‐based ranking models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 433-445, August.
  13. Will Ma, 2023. "When Is Assortment Optimization Optimal?," Management Science, INFORMS, vol. 69(4), pages 2088-2105, April.
  14. Beaudoin, David & Swartz, Tim, 2018. "A computationally intensive ranking system for paired comparison data," Operations Research Perspectives, Elsevier, vol. 5(C), pages 105-112.
  15. Vladimír Holý & Jan Zouhar, 2022. "Modelling time‐varying rankings with autoregressive and score‐driven dynamics," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1427-1450, November.
  16. Xiao-Yue Gong & Vineet Goyal & Garud N. Iyengar & David Simchi-Levi & Rajan Udwani & Shuangyu Wang, 2022. "Online Assortment Optimization with Reusable Resources," Management Science, INFORMS, vol. 68(7), pages 4772-4785, July.
  17. Cristina Mollica & Luca Tardella, 2017. "Bayesian Plackett–Luce Mixture Models for Partially Ranked Data," Psychometrika, Springer;The Psychometric Society, vol. 82(2), pages 442-458, June.
  18. Gerardo Berbeglia & Alvaro Flores & Guillermo Gallego, 2021. "The Refined Assortment Optimization Problem," Papers 2102.03043, arXiv.org.
  19. Marie-Louise Lackner & Martin Lackner, 2017. "On the likelihood of single-peaked preferences," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 48(4), pages 717-745, April.
  20. Juan Camilo Cardenas & Rajiv Sethi, 2010. "Resource Allocation in Public Agencies: Experimental Evidence," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 12(4), pages 815-836, August.
  21. Yazidi, Anis & Ivanovska, Magdalena & Zennaro, Fabio M. & Lind, Pedro G. & Viedma, Enrique Herrera, 2022. "A new decision making model based on Rank Centrality for GDM with fuzzy preference relations," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1030-1041.
  22. Biernacki, Christophe & Jacques, Julien, 2013. "A generative model for rank data based on insertion sort algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 162-176.
  23. Cristina Mollica & Luca Tardella, 2021. "Bayesian analysis of ranking data with the Extended Plackett–Luce model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 175-194, March.
  24. Dipankar Das, 2023. "A Model of Competitive Assortment Planning Algorithm," Papers 2307.09479, arXiv.org.
  25. Sahand Negahban & Sewoong Oh & Devavrat Shah, 2017. "Rank Centrality: Ranking from Pairwise Comparisons," Operations Research, INFORMS, vol. 65(1), pages 266-287, February.
  26. Antoine Désir & Vineet Goyal & Danny Segev & Chun Ye, 2020. "Constrained Assortment Optimization Under the Markov Chain–based Choice Model," Management Science, INFORMS, vol. 66(2), pages 698-721, February.
  27. Ben Aoki-Sherwood & Catherine Bregou & David Liben-Nowell & Kiran Tomlinson & Thomas Zeng, 2024. "Bounding Consideration Probabilities in Consider-Then-Choose Ranking Models," Papers 2401.11016, arXiv.org.
  28. Ali Aouad & Danny Segev, 2021. "Display Optimization for Vertically Differentiated Locations Under Multinomial Logit Preferences," Management Science, INFORMS, vol. 67(6), pages 3519-3550, June.
  29. R. Henery, 1992. "Unfolding and group consensus ranking for individual preferences," Journal of Classification, Springer;The Classification Society, vol. 9(1), pages 176-178, January.
  30. Juan Camilo Cárdenas & Rajiv Sethi, 2007. "Attitudes and attributes: a field experiment with public officials and transfer recipients In Colombia," Documentos CEDE 6881, Universidad de los Andes, Facultad de Economía, CEDE.
  31. Zhaonan Qu & Alfred Galichon & Johan Ugander, 2023. "On Sinkhorn's Algorithm and Choice Modeling," Papers 2310.00260, arXiv.org.
  32. Ekhine Irurozki & Borja Calvo & Jose A. Lozano, 2018. "Sampling and Learning Mallows and Generalized Mallows Models Under the Cayley Distance," Methodology and Computing in Applied Probability, Springer, vol. 20(1), pages 1-35, March.
  33. Sahand Negahban & Sewoong Oh & Devavrat Shah, 2017. "Rank Centrality: Ranking from Pairwise Comparisons," Operations Research, INFORMS, vol. 65(1), pages 266-287, February.
  34. Jose Blanchet & Guillermo Gallego & Vineet Goyal, 2016. "A Markov Chain Approximation to Choice Modeling," Operations Research, INFORMS, vol. 64(4), pages 886-905, August.
  35. Švendová, Vendula & Schimek, Michael G., 2017. "A novel method for estimating the common signals for consensus across multiple ranked lists," Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 122-135.
  36. Ali, Alnur & Meilă, Marina, 2012. "Experiments with Kemeny ranking: What works when?," Mathematical Social Sciences, Elsevier, vol. 64(1), pages 28-40.
  37. Santiago R. Balseiro & Antoine Désir, 2023. "Incentive-Compatible Assortment Optimization for Sponsored Products," Management Science, INFORMS, vol. 69(8), pages 4668-4684, August.
  38. Occelli, M. & Compaore, E. & Brown, D. & Barry, F. & Poda, L.S. & Traore, F. & Waongo, A. & Rubin, D. & Tufan, H.A., 2024. "Ex-ante priority setting in crop breeding: Towards inclusive innovation for impact," Agricultural Systems, Elsevier, vol. 217(C).
  39. Iannario, Maria & Piccolo, Domenico, 2014. "A theorem on CUB models for rank data," Statistics & Probability Letters, Elsevier, vol. 91(C), pages 27-31.
  40. Dirk van Straaten & René Fahr, 2021. "Fighting Fire with Fire - Overcoming Ambiguity Aversion by Introducing more Ambiguity," Working Papers Dissertations 73, Paderborn University, Faculty of Business Administration and Economics.
  41. Patrick Ding & Guido Imbens & Zhaonan Qu & Yinyu Ye, 2024. "Computationally Efficient Estimation of Large Probit Models," Papers 2407.09371, arXiv.org, revised Sep 2024.
  42. Federico Fioravanti & Iyad Rahwan & Fernando Abel Tohm'e, 2022. "Classes of Aggregation Rules for Ethical Decision Making in Automated Systems," Papers 2206.05160, arXiv.org, revised Jun 2023.
  43. Wu, Ping & Koop, Gary, 2023. "Estimating the ordering of variables in a VAR using a Plackett–Luce prior," Economics Letters, Elsevier, vol. 230(C).
  44. Holý, Vladimír, 2024. "Ranking-based second stage in data envelopment analysis: An application to research efficiency in higher education," Operations Research Perspectives, Elsevier, vol. 12(C).
  45. Yoo, Yeawon & Escobedo, Adolfo R. & Skolfield, J. Kyle, 2020. "A new correlation coefficient for comparing and aggregating non-strict and incomplete rankings," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1025-1041.
  46. Federico Fioravanti & Iyad Rahwan & Fernando Tohmé, 2022. "Properties of Aggregation Operators Relevant for Ethical Decision Making in Artificial Intelligence," Working Papers 177, Red Nacional de Investigadores en Economía (RedNIE).
  47. Theja Tulabandhula & Deeksha Sinha & Saketh Reddy Karra & Prasoon Patidar, 2020. "Multi-Purchase Behavior: Modeling, Estimation and Optimization," Papers 2006.08055, arXiv.org, revised Aug 2023.
  48. Shipra Agrawal & Vashist Avadhanula & Vineet Goyal & Assaf Zeevi, 2019. "MNL-Bandit: A Dynamic Learning Approach to Assortment Selection," Operations Research, INFORMS, vol. 67(5), pages 1453-1485, September.
  49. Lyubov Doroshenko & Brunero Liseo, 2023. "Generalized linear mixed model with bayesian rank likelihood," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(2), pages 425-446, June.
  50. 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.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.