|Authors:||Zhaozhi Qian, Philip L. H. Yu|
|Title:||Weighted Distance-Based Models for Ranking Data Using the R Package rankdist|
|Abstract:||rankdist is a recently developed R package which implements various distance-based ranking models. These models capture the occurring probability of rankings based on the distances between them. The package provides a framework for fitting and evaluating finite mixture of distance-based models. This paper also presents a new probability model for ranking data based on a new notion of weighted Kendall distance. The new model is flexible and more interpretable than the existing models. We show that the new model has an analytic form of the probability mass function and the maximum likelihood estimates of the model parameters can be obtained efficiently even for ranking involving a large number of objects.|
Page views:: 1787. Submitted: 2015-10-14. Published: 2019-07-31.
Weighted Distance-Based Models for Ranking Data Using the R Package rankdist
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.