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Модель Брэдли-Терри×Логистическая регрессия×Модель Плaкетта-Льюса×
ОбластьПринятие решенийСтатистика исследованийПринятие решений
СемействоRegression modelProcess / pipelineRegression model
Год появления195219581975
Автор методаRalph Bradley & Milton TerryDavid Roxbee CoxRobin Plackett; R. Duncan Luce
ТипProbabilistic paired comparison modelMethodProbabilistic ranking model
Основополагающий источникBradley, R. A., & Terry, M. E. (1952). Rank analysis of incomplete block designs: I. The method of paired comparisons. Biometrika, 39(3/4), 324–345. DOI ↗Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗Plackett, R. L. (1975). The analysis of permutations. Journal of the Royal Statistical Society: Series C, 24(2), 193–202. DOI ↗
Другие названияBT Model, Bradley-Terry-Luce Model, Paired Comparison Model, İkili Karşılaştırma Modelilogit model, binomial logistic regression, LRLuce's Choice Axiom Model, Rank-Ordered Logit Model, Exploded Logit Model, Sıralama Tercih Modeli
Связанные333
СводкаThe Bradley-Terry model is a probabilistic model for paired comparisons that assigns a latent strength parameter to each item and predicts the probability that one item beats another in a head-to-head contest. Introduced by Ralph A. Bradley and Milton E. Terry in 1952, it provides a principled statistical framework for ranking items from pairwise preference data, including incomplete comparison designs where not every pair is directly observed.Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science.The Plackett-Luce model is a probabilistic framework for analysing and predicting rank-ordered data. Introduced by Robin Plackett (1975) — building on R. Duncan Luce's earlier axiom of choice (1959) — it models the probability of any complete ranking of items as a sequential selection process, where each item's chance of being chosen at each position is proportional to its latent worth parameter. It is widely used in preference learning, recommender systems, and choice modelling.
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ScholarGateСравнение методов: Bradley-Terry Model · Logistic Regression · Plackett-Luce Model. Получено 2026-06-19 из https://scholargate.app/ru/compare