Time‐varying rankings with the Bayesian Mallows model

作者：Derbachew Asfaw; Valeria Vitelli; ystein Srensen; Elja Arjas; Arnoldo Frigessi

来源：Stat, 2017, 6(1): 14-30.

DOI：10.1002/sta4.132

• Bayesian data augmentation
• footrule distance
• incomplete rank data
• Mallows model
• MCMC
• preference prediction

We present new statistical methodology for analysing rank data, where the rankings are allowed to vary in time. Such data arise, for example, when the assessments are based on a performance measure of the items, which varies in time, or if the criteria, according to which the items are ranked, chang...