Discussion meetings

Discussion Meetings are events where articles 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.

***RSS Discussion meeting on Data Visualisation - CALL FOR CONTRIBUTED PAPERS***

The Society plans to hold a Discussion Meeting on Data Visualisation in late 2017 or early 2018 and is now inviting submissions for inclusion in the programme for the meeting. Effective data visualisation draws on many disciplines, including statistics, informatics, design and cognitive psychology. We welcome submissions from all of these, and other, disciplinary perspectives.

See our Callouts to members page on StatsLife for further details.

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.

Preprint discussion papers

2017

RSS Discussion Meeting, Wednesday, 12 April 2017
'Beyond subjective and objective in statistics'
Andrew Gelman and Christian Hennig
Details

RSS Discussion Meeting, Wednesday 15 March 2017
'Random-projection ensemble classification’
Timothy I. Cannings and Richard J. Samworth, University of Cambridge, UK
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

RSS Discussion Meeting, Wednesday, 12 April 2017

Andrew Gelman (Columbia University, New York) and Christian Hennig (University College London)

'Beyond subjective and objective in statistics'

Decisions in statistical data analysis are often justified, criticized or avoided by using concepts of objectivity and subjectivity. We argue that the words ‘objective’ and ‘subjective’ in statistics discourse are used in a mostly unhelpful way, and we propose to replace each of them with broader collections of attributes, with objectivity replaced by transparency, consensus, impartiality and correspondence to observable reality, and subjectivity replaced by awareness of multiple perspectives and context dependence. Together with stability, these make up a collection of virtues that we think is helpful in discussions of statistical foundations and practice. The advantage of these reformulations is that the replacement terms do not oppose each other and that they give more specific guidance about what statistical science strives to achieve. Instead of debating over whether a given statistical method is subjective or objective (or normatively debating the relative merits of subjectivity and objectivity in statistical practice), we can recognize desirable attributes such as transparency and acknowledgement of multiple perspectives as complementary goals. We demonstrate the implications of our proposal with recent applied examples from pharmacology, election polling and socio-economic stratification. The aim of the paper is to push users and developers of statistical methods towards more effective use of diverse sources of information and more open acknowledgement of assumptions and goals.

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

The preprint is available to download
'Beyond subjective and objective in statistics' (PDF)


RSS Discussion Meeting, Wednesday 15 March 2017

Timothy I. Cannings and Richard J. Samworth, University of Cambridge, UK

'Random-projection ensemble classification

We introduce a very general method for high dimensional classification, based on careful combination of the results of applying an arbitrary base classifier to random projections of the feature vectors into a lower dimensional space. In one special case that we study in detail, the random projections are divided into disjoint groups, and within each group we select the projection yielding the smallest estimate of the test error. Our random projection ensemble classifier then aggregates the results of applying the base classifier on the selected projections, with a data-driven voting threshold to determine the final assignment. Our theoretical results elucidate the effect on performance of increasing the number of projections. Moreover, under a boundary condition that is implied by the sufficient dimension reduction assumption, we show that the test excess risk of the random-projection ensemble classifier can be controlled by terms that do not depend on the original data dimension and a term that becomes negligible as the number of projections increases. The classifier is also compared empirically with several other popular high dimensional classifiers via an extensive simulation study, which reveals its excellent finite sample performance.

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

The preprint is available to download
'Random-projection ensemble classification’ (PDF) 
Supporting information (PDF)
Data and code (Zip file)