Discussion meetings

Discussion Meetings are events where articles ('papers for reading') appearing in the Journal of the Royal Statistical Society are presented and discussed. The discussion and authors' replies are then published in the relevant Journal series. About half of the meetings are organised by the Society's Research Section and the events are often preceded by an informal session on the issues raised by the papers.

Preprints of journal papers are available to download to encourage discussion at our Discussion Meetings before publication in one of our journals. Other papers, such as Presidential addresses, are also available to download. All preprints available here are provisional and subject to later amendment by the authors.


Contact Judith Shorten if you would like to make a written contribution to a discussion meeting or receive a preprint for each meeting by email.

Click here to watch videos from past discussion meetings.

Click here to submit a discussion paper.

Preprint discussion papers

2017

Research Section Discussion Meeting, Wednesday, 10 May 2017
'Sparse graphs using exchangeable random measures’
François Caron and Emily B Fox
Details

Presidential addresses

The Address of the president, Wednesday 24 June 2015
P J Diggle
Download ‘Statistics: a data science for the 21st century’ (PDF)

The Address of the president, Wednesday 26 June 2013
J Pullinger
Download ‘Statistics making an impact’ (PDF)

The Address of the president, Wednesday 7 December 2011
V Isham
Download ‘The evolving Society: united we stand’ (PDF)

The Address of the president, Wednesday 10 December 2008
D J Hand
Download ‘Modern statistics: the myth and the magic’ (PDF)

The Address of the president, Wednesday 12 December 2007
D Tim Holt
Download ‘Official statistics, public policy and public trust’ (PDF)

The Address of the president, Wednesday 15 June 2005
A P Grieve
Download ‘The professionalization of the shoe clerk’ (PDF)

Preprints

2017

Research Section Discussion Meeting, Wednesday, 10 May 2017

François Caron and Emily B Fox

‘Sparse graphs using exchangeable random measures’

Statistical network modelling has focused on representing the graph as a discrete structure, namely the adjacency matrix. When assuming exchangeability of this array—which can aid in modelling, computations, and theoretical analysis—the Aldous-Hoover theorem informs us that the graph is necessarily either dense or empty. We instead consider representing the graph as an exchangeable random measure and appeal to the Kallenberg representation theorem for this object. We explore using completely random measures (CRMs) to define the exchangeable random measure and we show how our CRM construction enables us to achieve sparse graphs while maintaining the attractive properties of exchangeability. We relate the sparsity of the graph to the Lévy measure defining the CRM. For a specific choice of CRM, our graphs can be tuned from dense to sparse on the basis of a single parameter. We present a scalable Hamiltonian Monte Carlo algorithm for posterior inference, which we use to analyse network properties in a range of real data sets, including networks with hundreds of thousands of nodes and millions of edges.

To be published in Series B, for more information go to the Wiley Online Library.

The preprint is available to download
'Sparse graphs using exchangeable random measures' (PDF)

Code (zip file)