Matlab/Octave package: BNPPL
Bayesian nonparametric Plackett-Luce for ranking data

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Link to the demo (html)


This Matlab/Octave package implements sampling algorithms for simulation and Bayesian inference in (mixture of) nonparametric Plackett-Luce models (Caron et al., 2014). These models are useful for analysing partial ranking data consisting of ordered lists of top-m items among a very large, potentially unbounded set of items.

The package has been tested on Matlab R2014a (with statistics toolbox) and Octave 3.6.4.

F. Caron, Y.W. Teh, T.B. Murphy. Bayesian nonparametric Plackett-Luce models for the analysis of preferences for college degree programmes. The Annals of Applied Statistics, vol. 8, no2, pp. 1145-1181, 2014. Download paper.


Demo of the package
Sampler and inference in nonparametric Plackett-Luce
Sampler and inference in mixture of nonparametric Plackett-Luce
Processing of the outputs of the MCMC algorithms

Latest corrections

Last update: 04-07-2014. Correction of a bug in clust_est_binder.m


(C) Copyright 2014 François Caron,University of Oxford
Permission is granted for anyone to copy, use, or modify these programs and accompanying documents for purposes of research or education, 
provided this copyright notice is retained, and note is made of any changes that have been made.

These programs and documents are distributed without any warranty, express or implied.
As the programs were written for research purposes only, they have not been tested to the degree that would be advisable in any important application.
All use of these programs is entirely at the user's own risk.