Arnak Dalalyan at the RSS Journal Webinar

My friend and CREST colleague Arnak Dalalyan will (re)present [online] a Read Paper at the RSS on 31 October with my friends Hani Doss and Alain Durmus as discussants:

‘Theoretical Guarantees for Approximate Sampling and Log-Concave Densities’

Arnak Dalalyan ENSAE Paris, France

Sampling from various kinds of distributions is an issue of paramount importance in statistics since it is often the key ingredient for constructing estimators, test procedures or confidence intervals. In many situations, exact sampling from a given distribution is impossible or computationally expensive and, therefore, one needs to resort to approximate sampling strategies. However, there is no well-developed theory providing meaningful non-asymptotic guarantees for the approximate sampling procedures, especially in high dimensional problems. The paper makes some progress in this direction by considering the problem of sampling from a distribution having a smooth and log-concave density defined on ℝᵖ⁠, for some integer p > 0. We establish non-asymptotic bounds for the error of approximating the target distribution by the distribution obtained by the Langevin Monte Carlo method and its variants. We illustrate the effectiveness of the established guarantees with various experiments. Underlying our analysis are insights from the theory of continuous time diffusion processes, which may be of interest beyond the framework of log-concave densities that are considered in the present work.

statistical aspects of climate change [discuss]

As part of its annual conference in Aberdeen, Scotland, the RSS is organising a discussion meeting on two papers presented on Wednesday 14 September 2022, 5.00PM – 7.00PM (GMT+1), with free on-line registration.

Two papers will be presented:

‘Assessing present and future risk of water damage using building attributes, meteorology, and topography’ by Heinrich-Mertsching et al.​
‘The importance of context in extreme value analysis with application to extreme temperatures in the USA and Greenland’ by Clarkson et al.​

“The Discussion Meeting at this year’s RSS conference in Aberdeen will feature two papers on the Statistical Aspects of Climate Change. The Discussion Meetings Committee chose this topic area motivated by the UN Climate Change Conference (COP26) held in Glasgow last year and because climate changes and the environment is one of the RSS’s six current campaigning priorities for 2022.

You are welcome to listen to the speakers and join in the discussion of the papers which follows the presentations. All the proceedings will be published in a forthcoming issue of Journal of the Royal Statistical Society, Series C (Applied Statistics) .”

Dr Shirley Coleman, Chair and Honorary Officer for Discussion Meetings

RSS COVID evidence sessions

The Royal Statistical Society is launching a series of discussions linked with the UK Government handling of the COVID-19 pandemic (and of the related data):

• Communication during the pandemic: Data, statistical analyses and modelling, 5 April
  Organising panel of David Spiegelhalter, Tom Chivers and Jen Rogers
  Register for the in-person or online event
• Governments’ statistical resources, 3 May
  Organising panel of Simon Briscoe and Gavin Freeguard
• Evidence and policy, 21 June
  Organising panel of Sylvia Richardson, Dani De Angelis and John Aston
• Evaluation, 12 July
  Organising panel of Sheila Bird, Christl Donnelly and Max Parmar.

 

RSS 2022 Honours

Scrapping Covid surveillance study would put public health at risk [by Silvia Richardson]

Royal Statistical Society president (and very dear friend) Sylvia Richardson published this tribune in the Guardian defending the preservation of a national surveillance system last week:

Sajid Javid is right to argue against scrapping the Office for National Statistics’ Covid surveillance study. Throughout the pandemic, national surveillance studies have provided invaluable information to support decision-making.

For any real-time health surveillance system to be reliable and cost-effective, it cannot rely solely on self-reported tests. These data sets are likely to be biased, as it is impossible to know how many people are also reporting their negative results and, if tests start to come with a cost, how many people simply aren’t testing. If we are to get reliable information about the prevalence of Covid, it is essential to maintain studies such as the ONS’s and React to allow statisticians to estimate infectiousness and the proportion of the population who are infected (including those without symptoms), as well as to identify new variants.

Abrupt disruption of a surveillance system is wasteful, will make tracking of prevalence meaningless and will put in jeopardy the future health of the public. If important surveillance studies must be scaled down, this cannot be led by arbitrary cost-cutting targets, but should be led by statisticians to ensure that studies continue to provide reliable information.