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. See our guidelines for papers for discussion.

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.

Preprint discussion papers

2018

Official Statistics Section Discussion Meeting, Wednesday, 9 May 2018

‘From start to finish: a framework for the production of small area official statistics’
Nikos Tzavidis, Li-Chun Zhang, Angela Luna, Timo Schmid and Natalia Rojas-Perilla
Details

Discussion Meeting, Wednesday, 18 April 2018

‘The statistical analysis of acoustic phonetic data: exploring differences between spoken Romance languages’
Davide Pigoli, Pantelis Z Hadjipantelis, John S Coleman and John A D Aston
Details

Discussion Meeting, Wednesday, 14 March 2018

‘Optimal treatment allocations in space and time for on-line control of an emerging infectious disease’
Eric B Laber, Nick J Meyer, Brian J Reich, Krishna Pacifici, Jaime A Collazo and John Drake
Details

2017

Official Statistics Section Discussion Meeting, Wednesday, 15 November 2017
‘Statistical challenges of administrative and transaction data’
David J Hand
Details

Preprints

2018

Official Statistics Section Discussion Meeting, Wednesday, 9 May 2018

Nikos Tzavidis, Li-Chun Zhang and Angela Luna (University of Southampton) and Timo Schmid and Natalia Rojas-Perilla (Free University, Berlin)

‘From start to finish: a framework for the production of small area official statistics’

Small area estimation is a research area in official and survey statistics of great practical relevance for national statistical institutes and related organizations. Despite rapid developments in methodology and software, researchers and users would benefit from having practical guidelines for the process of small area estimation. We propose a general framework for the production of small area statistics that is governed by the principle of parsimony and is based on three broadly defined stages, namely specification, analysis and adaptation, and evaluation. Emphasis is given to the interaction between a user of small area statistics and the statistician in specifying the target geography and parameters in the light of the available data. Model-free and model-dependent methods are described with a focus on model selection and testing, model diagnostics and adaptations such as use of data transformations. Uncertainty measures and the use of model and design-based simulations for method evaluation are also at the centre of the paper. We illustrate the application of the proposed framework by using real data for the estimation of non-linear deprivation indicators. Linear statistics, e.g. averages, are included as special cases of the general framework.

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

The preprint is available to download.
‘From start to finish: a framework for the production of small area official statistics’ (PDF)
Data and computer code (.zip)


Discussion Meeting, Wednesday, 18 April 2018

Davide Pigoli, Pantelis Z Hadjipantelis, John S Coleman and John A D Aston

'The statistical analysis of acoustic phonetic data: exploring differences between spoken Romance languages’

The historical and geographical spread from older to more modern languages has long been studied by examining textual changes and in terms of changes in phonetic transcriptions. However, it is more difficult to analyse language change from an acoustic point of view, although this is usually the dominant mode of transmission. We propose a novel analysis approach for acoustic phonetic data, where the aim will be to model the acoustic properties of spoken words statistically. We explore phonetic variation and change by using a time–frequency representation, namely the log-spectrograms of speech recordings. We identify time and frequency covariance functions as a feature of the language; in contrast, mean spectrograms depend mostly on the particular word that has been uttered. We build models for the mean and covariances (taking into account the restrictions placed on the statistical analysis of such objects) and use these to define a phonetic transformation that models how an individual speaker would sound in a different language, allowing the exploration of phonetic differences between languages. Finally, we map back these transformations to the domain of sound recordings, enabling us to listen to the output of the statistical analysis. The approach proposed is demonstrated by using recordings of the words corresponding to the numbers from 1 to 10 as pronounced by speakers from five different Romance languages.

To be published in Series C; for more information go to the Wiley Online Library.

The preprint is available to download.
The statistical analysis of acoustic phonetic data: exploring differences between spoken Romance languages’ (PDF)
Supporting information (PDF)


Discussion Meeting, Wednesday, 14 March 2018

Eric B Laber, Nick J Meyer, Brian J Reich, Krishna Pacifici (North Carolina State University, Raleigh), Jaime A Collazo (US Geological Survey North Carolina Fish and Wildlife Research Unit and North Carolina State University, Raleigh) and John Drake (University of Georgia, Athens)

‘Optimal treatment allocations in space and time for on-line control of an emerging infectious disease’

A key component in controlling the spread of an epidemic is deciding where, when and to whom to apply an intervention. We develop a framework for using data to inform these decisions in realtime. We formalize a treatment allocation strategy as a sequence of functions, one per treatment period, that map up-to-date information on the spread of an infectious disease to a subset of locations where treatment should be allocated. An optimal allocation strategy optimizes some cumulative outcome, e.g. the number of uninfected locations, the geographic footprint of the disease or the cost of the epidemic. Estimation of an optimal allocation strategy for an emerging infectious disease is challenging because spatial proximity induces interference between locations and the number of possible allocations is exponential in the number of locations, and because disease dynamics and intervention effectiveness are unknown at outbreak. We derive a Bayesian on-line estimator of the optimal allocation strategy that combines simulation–optimization with Thompson sampling. The estimator proposed performs favourably in simulation experiments. This work is motivated by and illustrated using data on the spread of white nose syndrome, which is a highly fatal infectious disease devastating bat populations in North America.

To be published in Series C; for more information go to the Wiley Online Library.

The preprint is available to download.
Optimal treatment allocations in space and time for on-line control of an emerging infectious disease’ (PDF)
Supporting information (PDF)
Data and computer code (.zip)


2017

Official Statistics Section Discussion Meeting, Wednesday, 15 November 2017

David J Hand

‘Statistical challenges of administrative and transaction data’

Administrative data are becoming increasingly important. They are typically the side effect of some operational exercise and are often seen as having significant advantages over alternative sources of data. Although it is true that such data have merits, statisticians should approach the analysis of such data with the same cautious and critical eye as they approach the analysis of data from any other source. The paper identifies some statistical challenges, with the aim of stimulating debate about and improving the analysis of administrative data, and encouraging methodology researchers to explore some of the important statistical problems which arise with such data.

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

The preprint is available to download
'Statistical challenges of administrative and transaction data' (PDF), Watch video (YouTube)