This book grew out of a desire on the part of both authors to formally record in one volume
some of their research on ranking methods. My own interest was sparked by a problem …

A mixture model for preferences data, which adequately represents the composite nature of
the elicitation mechanism in ranking processes, is proposed. Both probabilistic features of …

Ranking is one of the simple and efficient data collection techniques to understand
individuals' perception and preferences for some items such as products, people, and …

Cable cars are a viable alternative to improve citizens' accessibility in zones with limitations
on urban public transport supply due to the topography. In Latin America, such systems have …

Ranking data has applications in different fields of studies, like marketing, psychology and
politics. Over the years, many models for ranking data have been developed. Among them …

We develop a Bayesian method for aggregating partial ranking data using the Thurstone
model. Our implementation is a JAGS graphical model that allows each individual to rank …

Bayesian Analysis of Rank Data with Covariates and Heterogeneous Rankers Page 1 Statistical
Science 2022, Vol. 37, No. 1, 1–23 https://doi.org/10.1214/20-STS818 © Institute of Mathematical …

Ranking and rating methods for preference data result in a different underlying organization
of data that can lead to manifold probabilistic approaches to data modelling. As an …

Abstract We propose the Heterogeneous Thurstone Model (HTM) for aggregating ranked
data, which can take the accuracy levels of different users into account. By allowing different …

A Thurstonian model for ranking data assumes that observed rankings are consistent with
those of a set of underlying continuous variables. This model is appealing since it renders …