Relevant bibliographies by topics / Bradley Terry models

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  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Bradley Terry models'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Bradley Terry models"

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Hunter, David R. "MM algorithms for generalized Bradley-Terry models." Annals of Statistics 32, no. 1 (2003): 384–406. http://dx.doi.org/10.1214/aos/1079120141.

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Caron, François, and Arnaud Doucet. "Efficient Bayesian Inference for Generalized Bradley–Terry Models." Journal of Computational and Graphical Statistics 21, no. 1 (2012): 174–96. http://dx.doi.org/10.1080/10618600.2012.638220.

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Tutz, Gerhard. "Bradley-Terry-Luce models with an ordered response." Journal of Mathematical Psychology 30, no. 3 (1986): 306–16. http://dx.doi.org/10.1016/0022-2496(86)90034-9.

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Casalicchio, Giuseppe, Gerhard Tutz, and Gunther Schauberger. "Subject-specific Bradley–Terry–Luce models with implicit variable selection." Statistical Modelling: An International Journal 15, no. 6 (2015): 526–47. http://dx.doi.org/10.1177/1471082x15571817.

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Fujimoto, Yu, Hideitsu Hino, and Noboru Murata. "An Estimation of Generalized Bradley-Terry Models Based on the em Algorithm." Neural Computation 23, no. 6 (2011): 1623–59. http://dx.doi.org/10.1162/neco_a_00129.

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The Bradley-Terry model is a statistical representation for one's preference or ranking data by using pairwise comparison results of items. For estimation of the model, several methods based on the sum of weighted Kullback-Leibler divergences have been proposed from various contexts. The purpose of this letter is to interpret an estimation mechanism of the Bradley-Terry model from the viewpoint of flatness, a fundamental notion used in information geometry. Based on this point of view, a new estimation method is proposed on a framework of the em algorithm. The proposed method is different in i
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Matthews, J. N. S., and K. P. Morris. "An Application of Bradley-Terry-Type Models to the Measurement of Pain." Applied Statistics 44, no. 2 (1995): 243. http://dx.doi.org/10.2307/2986348.

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Krese, Blaž, and Erik Štrumbelj. "A Bayesian approach to time-varying latent strengths in pairwise comparisons." PLOS ONE 16, no. 5 (2021): e0251945. http://dx.doi.org/10.1371/journal.pone.0251945.

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The famous Bradley-Terry model for pairwise comparisons is widely used for ranking objects and is often applied to sports data. In this paper we extend the Bradley-Terry model by allowing time-varying latent strengths of compared objects. The time component is modelled with barycentric rational interpolation and Gaussian processes. We also allow for the inclusion of additional information in the form of outcome probabilities. Our models are evaluated and compared on toy data set and real sports data from ATP tennis matches and NBA games. We demonstrated that using Gaussian processes is advanta
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Strobl, Carolin, Florian Wickelmaier, and Achim Zeileis. "Accounting for Individual Differences in Bradley-Terry Models by Means of Recursive Partitioning." Journal of Educational and Behavioral Statistics 36, no. 2 (2011): 135–53. http://dx.doi.org/10.3102/1076998609359791.

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Yan, Ting. "Ranking in the generalized Bradley–Terry models when the strong connection condition fails." Communications in Statistics - Theory and Methods 45, no. 2 (2016): 340–53. http://dx.doi.org/10.1080/03610926.2013.809114.

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Dittrich, R., W. Katzenbeisser, and H. Reisinger. "The analysis of rank ordered preference data based on Bradley-Terry Type Models." OR Spectrum 22, no. 1 (2000): 117–34. http://dx.doi.org/10.1007/s002910050008.

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Dissertations / Theses on the topic "Bradley Terry models"

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Hatzinger, Reinhold, and Brian Francis. "Fitting paired comparison models in R." Institut für Statistik und Mathematik, WU Vienna University of Economics and Business, 2004. http://epub.wu.ac.at/740/1/document.pdf.

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Paired comparison models in loglinear form are generalised linear models and can be fitted using the IWLS algorithm. Unfortunately, the design matrices can become very large and thus a method is needed to reduce computational load (relating to both space and time). This paper discusses an algorithm for fitting loglinear paired comparison models in the presence of many nuisance parameters which is based on partition rules for symmetric matrices and takes advantage of the special structure of the design matrix in Poisson loglinear models. The algorithm is implemented as an R function. Some simpl
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Matthews, Gregory J. "Improved paired comparison models for NFL point spreads by data transformation." Link to electronic thesis, 2005. http://www.wpi.edu/Pubs/ETD/Available/etd-050505-144934/.

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Hallinan, Shawn E. "Paired Comparison Models for Ranking National Soccer Teams." Link to electronic thesis, 2005. http://www.wpi.edu/Pubs/ETD/Available/etd-050505-154305/.

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Dittrich, Regina, Reinhold Hatzinger, and Walter Katzenbeisser. "Subject-Specific Covariates in the Bradley-Terry Model. A Log-Linear Approach." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 1996. http://epub.wu.ac.at/1026/1/document.pdf.

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The purpose of this paper is to give a log-linear representation of a generalized Bradley-Terry (BT-) Model for paired comparisons which allows the incorporation of ties, order effects, concomitant variables for the objects and categorical subject specific covariates and interactions between all of them. An advantage of this approach is that standard software for fitting log-linear models, such as GLIM, can be used. The approach is exemplified by analysing data from an experiment concerning the ranking of European universities. (author's abstract)<br>Series: Forschungsberichte / Institut für S
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Grand, Alexandra, and Regina Dittrich. "Modelling Assumed Metric Paired Comparison Data - Application to Learning Related Emotions." Austrian Statistical Society, 2015. http://epub.wu.ac.at/4762/1/Grand_Dittrich_2015_AJS_Modelling%2DAssumed%2DMetric_25%2D349%2D1%2DPB.pdf.

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In this article we suggest a beta regression model that accounts for the degree of preference in paired comparisons measured on a bounded metric paired comparison scale. The beta distribution for bounded continuous random variables assumes values in the open unit interval (0,1). However, in practice we will observe paired comparison responses that lie within a fixed or arbitrary fixed interval [-a,a] with known value of a. We therefore transform the observed responses into the interval (0,1) and assume that these transformed responses are each a realization of a random variable which follows a
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Girabent, i. Farrés Montserrat. "Aplicació dels models de Thrustone i de Bradely-Terry a l’anàlisi de dades “ranking” obtingudes de mesures de preferència en escala ipsativa." Doctoral thesis, Universitat de Barcelona, 2013. http://hdl.handle.net/10803/277566.

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La recerca va néixer de l’interès de mesurar les preferències dels individus quan se’ls demana que ordenin una llista d’opcions, ja siguin conductes o objectes, obtenint així dades rànquing. Això determina que l’individu està forçat a establir un ordre entre les seves preferències, donant lloc al que es coneix com a escala de mesura ipsativa ordinal. Aquest tipus de mesura té com a avantatge front a la d’escala normativa, com Likert, que disminueix la probabilitat del conegut problema d’ “acquiescense bias” i s’elimini l’efecte “halo and horn”. Per altre banda, la principal caracterís
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Menke, Joshua Ephraim. "Improving Machine Learning Through Oracle Learning." BYU ScholarsArchive, 2007. https://scholarsarchive.byu.edu/etd/843.

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The following dissertation presents a new paradigm for improving the training of machine learning algorithms, oracle learning. The main idea in oracle learning is that instead of training directly on a set of data, a learning model is trained to approximate a given oracle's behavior on a set of data. This can be beneficial in situations where it is easier to obtain an oracle than it is to use it at application time. It is shown that oracle learning can be applied to more effectively reduce the size of artificial neural networks, to more efficiently take advantage of domain experts by approxima
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Dittrich, Regina, Brian Francis, Reinhold Hatzinger, and Walter Katzenbeisser. "A Paired Comparison Approach for the Analysis of Sets of Likert Scale Responses." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 2005. http://epub.wu.ac.at/654/1/document.pdf.

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This paper provides an alternative methodology for the analysis of a set of Likert responses measured on a common attitudinal scale when the primary focus of interest is on the relative importance of items in the set. The method makes fewer assumptions about the distribution of the responses than the more usual approaches such as comparisons of means, MANOVA or ordinal data methods. The approach transforms the Likert responses into paired comparison responses between the items. The complete multivariate pattern of responses thus produced can be analysed by an appropriately reformulated paired
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Dittrich, Regina, Brian Francis, and Walter Katzenbeisser. "Temporal dependence in longitudinal paired comparisons." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 2008. http://epub.wu.ac.at/1452/1/document.pdf.

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This paper develops a new approach to the analysis of longitudinal paired comparison data, where comparisons of the same objects by the same judges are made on more than one occasion. As an alternative to other recent approaches to such data, which are based on Kalman filter- ing, our approach treats the problem as one of multivariate multinomial data, allowing dependence terms between comparisons over time to be incorporated. The resulting model can be fitted as a Poisson log-linear model and has parallels with the quadratic binary exponential distribution of Cox. An example from the British
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Rajkumar, Arun. "Ranking from Pairwise Comparisons : The Role of the Pairwise Preference Matrix." Thesis, 2016. http://etd.iisc.ernet.in/2005/3787.

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Ranking a set of candidates or items from pair-wise comparisons is a fundamental problem that arises in many settings such as elections, recommendation systems, sports team rankings, document rankings and so on. Indeed it is well known in the psychology literature that when a large number of items are to be ranked, it is easier for humans to give pair-wise comparisons as opposed to complete rankings. The problem of ranking from pair-wise comparisons has been studied in multiple communities such as machine learning, operations research, linear algebra, statistics etc., and several algorithms (b
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Book chapters on the topic "Bradley Terry models"

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Torsney, Ben. "Fitting Bradley Terry Models Using a Multiplicative Algorithm." In COMPSTAT 2004 — Proceedings in Computational Statistics. Physica-Verlag HD, 2004. http://dx.doi.org/10.1007/978-3-7908-2656-2_42.

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Stein, Alfred, Arko Lucieer, and Gerrit Gort. "Use of the Bradley-Terry Model to Assess Uncertainty in an Error Matrix from a Hierarchical Segmentation of an ASTER Image." In Signal and Image Processing for Remote Sensing. CRC Press, 2006. http://dx.doi.org/10.1201/9781420003130.ch26.

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"Use of the Bradley–Terry Model to Assess Uncertainty in an Error Matrix from a Hierarchical Segmentation of an ASTER Image." In Image Processing for Remote Sensing. CRC Press, 2007. http://dx.doi.org/10.1201/9781420066654-20.

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"Use of the Bradley–Terry Model to Assess Uncertainty in an Error Matrix from a Hierarchical Segmentation of an ASTER Image." In Signal and Image Processing for Remote Sensing. CRC Press, 2006. http://dx.doi.org/10.1201/9781420003130-33.

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Conference papers on the topic "Bradley Terry models"

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Guo, Yuan, Peng Tian, Jayashree Kalpathy-Cramer, et al. "Experimental Design under the Bradley-Terry Model." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/304.

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Labels generated by human experts via comparisons exhibit smaller variance compared to traditional sample labels. Collecting comparison labels is challenging over large datasets, as the number of comparisons grows quadratically with the dataset size. We study the following experimental design problem: given a budget of expert comparisons, and a set of existing sample labels, we determine the comparison labels to collect that lead to the highest classification improvement. We study several experimental design objectives motivated by the Bradley-Terry model. The resulting optimization problems a
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Hu, Jun, and Ping Li. "Improved and Scalable Bradley-Terry Model for Collaborative Ranking." In 2016 IEEE 16th International Conference on Data Mining (ICDM). IEEE, 2016. http://dx.doi.org/10.1109/icdm.2016.0118.

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Takenouchi, Takashi, and Shin Ishii. "Ternary Bradley-Terry model-based decoding for multi-class classification." In 2008 IEEE Workshop on Machine Learning for Signal Processing (MLSP) (Formerly known as NNSP). IEEE, 2008. http://dx.doi.org/10.1109/mlsp.2008.4685466.

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Dae-Ki Kang and Myong-Jong Kim. "Poisson Model and Bradley terry Model for predicting multiplayer online battle games." In 2015 Seventh International Conference on Ubiquitous and Future Networks (ICUFN). IEEE, 2015. http://dx.doi.org/10.1109/icufn.2015.7182671.

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Cao, Binwen, Li Chen, and Hui Lie. "Vast Amounts of Video Data Clean Algorithm Base on Bradley-Terry Model." In 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016). Atlantis Press, 2017. http://dx.doi.org/10.2991/emcm-16.2017.21.

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Nor, Shahdiba Binti Md, and Zamalia Mahmud. "Teams ranking of Malaysia Super League using Bayesian expectation maximization for Generalized Bradley Terry Model." In THE 4TH INTERNATIONAL CONFERENCE ON QUANTITATIVE SCIENCES AND ITS APPLICATIONS (ICOQSIA 2016). Author(s), 2016. http://dx.doi.org/10.1063/1.4966101.

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Genest, Christian, and Cyr-Emile M'Ian. "Priorities Derived from Pairwise Preferences Via Saaty's Method and the Bradley-Terry Model: What is the Connection?" In The International Symposium on the Analytic Hierarchy Process. Creative Decisions Foundation, 1996. http://dx.doi.org/10.13033/isahp.y1996.052.

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