SuSTaIn - Statistics underpinning Science, Technology and Industry
Lead Research Organisation:
University of Bristol
Department Name: Mathematics
Abstract
Our judgment, and that of the recent International Review of UK Mathematics Research (IRM), is that significant capability in theoretical and mathematical statistics is small and in decline in the UK. This decline needs to be halted and reversed. Now is the time.SuSTaIn will be a centre that conducts and disseminates top-rank research in mathematical statistics, and implants it into the discipline of statistics in the UK. We will nurture SuSTaIn to build a strong capability in mathematical statistics within the supportive environment of the Statistics Group at Bristol University. The main pillars of our proposal are to (i) hire a strong dynamic team consisting of a Professor, and four early- to mid-career researchers as lecturers (ii) attract a number of postdoctoral fellows of outstanding potential onto a rolling programme where they are free to forge and develop the latest ideas in mathematical statistics, (iii) initiate a comprehensive 4-year MRes/PhD research training programme, (iv) conduct numerous activities (including kick-starting a major UK conference series in mathematical statistics ) to promote our vision for the discipline, and encourage its wider adoption in the UK.Bristol University is committed to strong financial and material support for this development, to enable this bid to succeed and the initiative to flourish, beyond the initial period of EPSRC/HEFCE funding.SuSTaIn is both about immediate initiation of advanced research in mathematical statistics generating a step change in UK activity and helping to ensure the future by the nurturing of staff and graduate students early on in their career. Bristol University's Statistics Group has a well-recognized reputation for research excellence in mathematical statistics and for providing an exciting and supportive environment. Both the excellence and the environment have contributed to the Group's success in attracting outstanding international researchers in the face of national recruitment difficulties.Mathematical statistics for the new century will thrive and develop a symbiotic relationship with the existing methodological focus of the Group. SuSTaIn will reach out to a wide range of collaborative ventures, making use of existing proven links as well as forging innovative new connections within a strong and diverse University. It will strengthen UK Statistics nationally and address global concerns arising from the `data revolution'. SuSTaIn will stimulate knowledge exchange both to and from Mathematics (on the theoretical side) and plug-in to the existing methodological Group which itself has established knowledge transfer routes to key scientific and engineering areas, for example, bioinformatics, data fusion and quantum information.
Publications
Altmann Y
(2015)
Bayesian Nonlinear Hyperspectral Unmixing With Spatial Residual Component Analysis
in IEEE Transactions on Computational Imaging
Altmann Y
(2015)
Collaborative sparse regression using spatially correlated supports--Application to hyperspectral unmixing.
in IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Armstrong CT
(2011)
SCORER 2.0: an algorithm for distinguishing parallel dimeric and trimeric coiled-coil sequences.
in Bioinformatics (Oxford, England)
Battey H
(2013)
Smooth projected density estimation
Bochkina N
(2014)
The Bernstein-von Mises theorem and nonregular models
in The Annals of Statistics
Bowsher C
(2012)
The Dynamics of Economic Functions: Modeling and Forecasting the Yield Curve
in Journal of the American Statistical Association
Bowsher CG
(2011)
Automated analysis of information processing, kinetic independence and modular architecture in biochemical networks using MIDIA.
in Bioinformatics (Oxford, England)
Bowsher CG
(2013)
The fidelity of dynamic signaling by noisy biomolecular networks.
in PLoS computational biology
Bowsher CG
(2014)
Environmental sensing, information transfer, and cellular decision-making.
in Current opinion in biotechnology
Dawid AP
(2014)
A Formal Treatment of Sequential Ignorability.
in Statistics in biosciences
Didelot X
(2011)
Likelihood-free estimation of model evidence
in Bayesian Analysis
Doucet A
(2010)
On solving integral equations using Markov chain Monte Carlo methods
in Applied Mathematics and Computation
Eckley I
(2010)
Locally Stationary Wavelet Fields with Application to the Modelling and Analysis of Image Texture
in Journal of the Royal Statistical Society Series C: Applied Statistics
Eckley Idris A.
(2011)
LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R
in JOURNAL OF STATISTICAL SOFTWARE
Eckley Idris A.
(2010)
Locally stationary wavelet fields with application to the modelling and analysis of image texture
in JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS
Everitt R
(2012)
Bayesian Parameter Estimation for Latent Markov Random Fields and Social Networks
in Journal of Computational and Graphical Statistics
Everitt R
(2013)
Online Bayesian Inference in Some Time-Frequency Representations of Non-Stationary Processes
in IEEE Transactions on Signal Processing
Forest C
(2008)
Inferring climate system properties using a computer model
in Bayesian Analysis
Goldstein M
(2009)
Reified Bayesian modelling and inference for physical systems
in Journal of Statistical Planning and Inference
Green P
(2013)
Sampling decomposable graphs using a Markov chain on junction trees
in Biometrika
Green P
(2015)
Bayesian computation: a summary of the current state, and samples backwards and forwards
in Statistics and Computing
Green P
(2009)
Sensitivity of inferences in forensic genetics to assumptions about founding genes
in The Annals of Applied Statistics
Heine Kari
(2014)
Butterfly resampling: asymptotics for particle filters with constrained interactions
in arXiv e-prints
Hosking FJ
(2008)
Inference from genome-wide association studies using a novel Markov model.
in Genetic epidemiology
Hurn M
(2008)
A Bayesian Hierarchical Model for Photometric Red Shifts
in Journal of the Royal Statistical Society Series C: Applied Statistics
Jankowski H
(2010)
Expectations of Random Sets and Their Boundaries Using Oriented Distance Functions
in Journal of Mathematical Imaging and Vision
Jankowski H
(2014)
A random set approach to confidence regions with applications to the effective dose with combinations of agents.
in Statistics in medicine
Jankowski H
(2012)
Identifying Skeleton Curves in Noisy Data
in Communications in Statistics - Simulation and Computation
JANKOWSKI H
(2012)
Confidence Regions for Means of Random Sets Using Oriented Distance Functions
in Scandinavian Journal of Statistics
Johansen A
(2010)
International Encyclopedia of Education
Johansen A
(2008)
A note on auxiliary particle filters
in Statistics & Probability Letters
Johansen A
(2010)
International Encyclopedia of Education
Lau J
(2007)
Bayesian Model-Based Clustering Procedures
in Journal of Computational and Graphical Statistics
Leslie D
(2020)
Best-response dynamics in zero-sum stochastic games
in Journal of Economic Theory
Liverani S
(2016)
Bayesian selection of graphical regulatory models
in International Journal of Approximate Reasoning
Mardia KV
(2007)
Bayesian refinement of protein functional site matching.
in BMC bioinformatics
Nason G
(2015)
Bayesian Wavelet Shrinkage of the Haar-Fisz Transformed Wavelet Periodogram.
in PloS one
Nieto-Reyes A
(2014)
A topologically valid definition of depth for functional data
Nieto-Reyes A
(2016)
A Topologically Valid Definition of Depth for Functional Data
in Statistical Science
Papastathopoulos I
(2016)
Conditional independence among max-stable laws
in Statistics & Probability Letters
Papastathopoulos I
(2014)
Dependence properties of multivariate max-stable distributions
in Journal of Multivariate Analysis
Papastathopoulos I
(2016)
Conditional independence and conditioned limit laws
in Statistics & Probability Letters
Papastathopoulos I
(2014)
Conditioned limit laws for inverted max-stable processes
Papastathopoulos I
(2017)
Extreme events of Markov chains
in Advances in Applied Probability
Papastathopoulos I
(2015)
Conditional independence and conditioned limit laws
Papastathopoulos I
(2015)
Stochastic Ordering Under Conditional Modelling of Extreme Values: Drug-Induced Liver Injury
in Journal of the Royal Statistical Society Series C: Applied Statistics
Description | The large grant was intended to boost UK research and capacity in mathematical statistics. Many detailed research findings are described on the publications page. A major outcome of this grant is the nurturing of a new generation of researchers in mathematical statistics and their deployment in UK statistics |
Exploitation Route | This was a large omnibus grant to boost research capacity in Statistics. In one way or another it supported over 150 people on various activities. It would be impossible to list all of the finding and possibilities to take the research forward |
Sectors | Aerospace Defence and Marine Agriculture Food and Drink Chemicals Communities and Social Services/Policy Construction Creative Economy Digital/Communication/Information Technologies (including Software) Education Electronics Energy Environment Financial Services and Management Consultancy Healthcare Leisure Activities including Sports Recreation and Tourism Government Democracy and Justice Manufacturing including Industrial Biotechology Culture Heritage Museums and Collections Pharmaceu |
URL | http://www.sustain.bris.ac.uk |
Description | This large grant supported an enormous range of research into mathematical statistics. The main point of the grant was CAPACITY BUILDING in the Statistical Sciences. The grant funded a large number of early and mid-career researchers many who have gone on to positions in academia and industry. The grant also funded a large number of international workshops and meetings attracting a wide range of participants from academia and industry. The grant was explicitly awarded to support blue-skies research into mathematical statistics to underpin future applications in science and industry. |
First Year Of Impact | 2006 |
Sector | Digital/Communication/Information Technologies (including Software) |
Impact Types | Cultural |
Description | MRC Biomedical informatics Fellowship. |
Amount | £1 (GBP) |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 03/2013 |
Description | /World Conference of the International Society for Bayesian Analysis |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Poster Valencia Meetings/World Conference of the International Society for Bayesian Analysis (ISBA), Spain (2010) Graphical Model Selection over Huge Profile Partition Spaces with Dependent Clusters |
Year(s) Of Engagement Activity | 2010 |
Description | Adam Johansen: Auxiliary Particle Methods |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Auxiliary Particle Methods, Oxford University - Man Institute Workshop on Monte Carlo Methods, 29th May 2008. |
Year(s) Of Engagement Activity | 2008 |
Description | Adam Johansen: Monte Carlo Filtering of Piecewise Deterministic Processes |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Monte Carlo Filtering of Piecewise Deterministic Processes, Warwick University - EPSRC Symposium Workshop on Markov Chain Monte Carlo and Related Methods |
Year(s) Of Engagement Activity | 2009 |
Description | Adam Johansen: Sequential Monte Carlo: Selected Methodological Applications |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Sequential Monte Carlo: Selected Methodological Applications. Warwick University - Centre for Scientific Computing, 9th March, 2009 |
Year(s) Of Engagement Activity | 2009 |
Description | Bayesian week in CIRM 2016 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Study participants or study members |
Results and Impact | Brunel Fellow invited speaker at Bayesian week in CIRM 2016 |
Year(s) Of Engagement Activity | 2016 |
Description | CFE-CMStatistics |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Study participants or study members |
Results and Impact | Brunel Fellow invited to speak at CFE-CMStatistics "On the properties of variational approximation to Gibbs measures" December 2015 |
Year(s) Of Engagement Activity | 2015 |
URL | http://cmstatistics.org/CMStatistics2016/ |
Description | Closing workshop |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Study participants or study members |
Results and Impact | This is the closing workshop of the SuSTaIn initiative (2006-2016). The aim of this workshop is to advance and disseminate the research spurred by SuSTaIn through the work of its personnel and seek new directions for the future. |
Year(s) Of Engagement Activity | 2016 |
URL | https://www.sustain.bris.ac.uk/ws-final/programme.html |
Description | Conference Presentation - Causal Inference in a Decision-Theoretic framework', University of Southampton, U.K.. |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Participants in your research and patient groups |
Results and Impact | N Constantinou presented at this conference N Constantinou presented at this conference in Southampton UK |
Year(s) Of Engagement Activity | 2014 |
Description | Conference presentation: Causal Inference, Graphical Models and Prediction, University of Cambridge, U.K.. |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Participants in your research and patient groups |
Results and Impact | N Constantinou presented a talk entitled : Conditional Independence in the Decision-Theoretic framework of Statistical Causality Conference Presentation |
Year(s) Of Engagement Activity | 2014 |
Description | Exchange & Networking project for Research Staff in Statistics |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Silvia Liverani was awarded funds (with Dino Sejdinovic) to organise an Exchange & Networking project for Research Staff in Statistics, University of Bristol (£750). We organised a series of talks at Bristol, Bath and Oxford. |
Year(s) Of Engagement Activity | 2010 |
Description | Hidden Complexities in Complex Traits and Genome-wide Association |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Genetics promises to help us understand the underlying evolutionary structure of complex traits and so give insight into the heritable component of many important diseases. However, scientific advances have remained incremental which suggests that current methodology is limited. Improved statistical methods and modelling will be key to making the most of existing data and preparing for the next generation of data. This workshop aims to bring together experts on the methodology underpinning the analysis of complex traits and their relationship to genetics and biological function. The focus will be at the cutting edge of the statistical analysis of complex traits data, its associated practical interpretation and the benefits to society at large. This workshop is organised by Dan Lawson, Mark Beaumont and Nic Timpson. |
Year(s) Of Engagement Activity | 2015 |
Description | High-dimensional Statistics, Inverse Problems and Convex Analysis |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | This workshop will bring together scientists from the statistics, applied mathematics, signal processing and machine learning communities around the topic of convex analysis and its application to challenging inverse problems. The workshop will feature invited talks by world-leading experts presenting cutting edge research on new theory, methodology, and computer algorithms. We aim to provide a valuable opportunity to network and to foster extensive future interaction between the these disciplines. This workshop is organised by Marcelo Pereyra and Carola-Bibiane Schönlieb |
Year(s) Of Engagement Activity | 2016 |
Description | High-dimensional Stochastic Simulation and Optimisation in Image Processing workshop |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Participants in your research and patient groups |
Results and Impact | The scope of this research workshop is stochastic simulation and optimisation in image processing (IP), with a particular focus on ill-posed inverse problems that are high-dimensional, have unknown parameters or involve intractable statistical models. With the recent development of fast and affordable imaging devices, digital images have become fundamental sources of information in science and industry. This has generated an abundance of challenging IP problems as well as the need for more complex image models and new methodologies to use them. Most modern IP methods rely strongly on statistical theory to solve IP problems, i.e., they use statistical models to describe the image observation process and obtain solutions by performing statistical inference (e.g., computing maximum likelihood or Bayesian estimates). This is mainly achieved by using optimisation techniques related to variational and convex minimisation, and simulation methods such as Markov chain Monte Carlo and Sequential Monte Carlo. This workshop will bring together world experts on statistical IP, computational statistics and optimisation to discuss the theoretical and methodological challenges facing future statistical IP. The aim is to promote transfer of ideas and methodologies and to identify opportunities for synergy between these important areas, in particular through the integration of stochastic simulation and modern optimisation techniques. The conference programme will include invited plenary talks, contributed research talks and poster presentations. The scope of the workshop includes basic theory and methods and algorithms, and applications in the following areas: Theory, methods and algorithms Stochastic simulation for high-dimensional and IP statistical models. Recent advances in convex optimisation methods for IP. Variational methods for statistical inference in IP. Computational methods for intractable models (e.g., pseudo-marginal MCMC, likelihood-free methods, stochastic gradient MCMC, etc.). General IP methodology for high-dimensional inverse problems with uknown parameters (e.g., blind, semi-blind, unsupervised problems). Application Areas Modelling and methodology for remote sensing applications Modelling and methodology for medical and biological applications |
Year(s) Of Engagement Activity | 2014 |
URL | http://www.sustain.bris.ac.uk/ws-image-processing/ |
Description | High-dimensional and Multivariate Extremes workshop |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Participants in your research and patient groups |
Results and Impact | The scope of this workshop is extreme value theory, methods and applications, with a particular focus on multivariate and high-dimensional extremes. Extreme value theory (EVT) focuses on the study and development of stochastic models that can be used for inference on applied problems related to the frequency of the unusual rather than the usual. There is now an extensive range of applications of EVT in many scientific disciplines in which most of them concern the long range prediction of extreme quantities of interest. Common applications among many others are in hydrology, oceanography, insurance and finance. In many applications, the problems concerning extremes are multivariate or can be high dimensional in nature. For example, in spatial extremes, an area of recent activity, complications arise from modelling extremes in infinite-dimensional spaces. These challenges often prove prohibitive since in order to estimate the joint tail, one typically relies on a small portion of the data. The aim of this event is to promote discussion and transferral of ideas and methodologies between researchers and practitioners working in the area of extremes, with experts highlighting the challenges and developments in their respective fields of specialisation. The scientific program will include invited plenary talks, contributed research talks and poster presentations. The agenda of the workshop includes theory, methodology and applications in the following areas: Classical extreme value theory Multivariate extremes and time series Stochastic processes Spatial extremes High-dimensional extremes and dimension reduction |
Year(s) Of Engagement Activity | 2014 |
URL | http://www.sustain.bris.ac.uk/ws-extremes/ |
Description | ICMS Workshop |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Study participants or study members |
Results and Impact | ICMS Workshop organised (co-organiser Prof Peter Swain Edinburgh) in Edinburgh summer of 2013 on 'Information, Probability and Inference in Systems Biology'. |
Year(s) Of Engagement Activity | 2013 |
Description | International Conference On Geometry And Graphics |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Jankowski, Stanberry. Visualizing Variability: Confidence Regions In Level Set Estimation. Proceedings Of The International Conference On Geometry And Graphics, At Innsbruck, Austria, August 2014 |
Year(s) Of Engagement Activity | 2014 |
Description | Sequential Monte Carlo Optimisation |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Sequential Monte Carlo Optimisation, Bristol University: Bridging the Gaps (Probabilistic Models for Optimisation), 28th November, 2007 |
Year(s) Of Engagement Activity | 2007 |
Description | Sequential Monte Carlo Samplers for Rare Events |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Sequential Monte Carlo Samplers for Rare Events,RESIM 2006, 10th October, 2006 |
Year(s) Of Engagement Activity | 2006 |
Description | Statistical Modelling and Inference for Networks: Statworks |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | SuSTaIn workshop: "Statistical Modelling and Inference for Networks: Statworks", June 2010, ~80 participants. |
Year(s) Of Engagement Activity | 2010 |
Description | SuSTaIn EdgeCutter One Day Workshop on Astrostatistics |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Participants in your research and patient groups |
Results and Impact | This workshop will present a selection of cutting edge international research in the rapidly growing discipline of Astrostatistics. The workshop will bring together statisticians who are interested in astronomy and astronomers who are interested in statistical methods. We aim to provide a valuable opportunity to network and to foster extensive future interaction between the two disciplines. |
Year(s) Of Engagement Activity | 2014 |
URL | http://www.sustain.bris.ac.uk/ws-astrostatistics/ |
Description | SuSTaIn i-like workshop "Intractable Likelihoods" |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Participants in your research and patient groups |
Results and Impact | In most statistical contexts, it is recognised that inference methodology based on the likelihood function are usually methods of choice. However such methods are not always easy to implement. For instance, in complex problems often with massive data sets, it can sometimes be completely impossible to even evaluate the likelihood function. The computational statistics revolution of the 1990s provided powerful methodology for carrying out likelihood-based inference, including Markov chain Monte Carlo methods, the EM algorithm, many associated optimisation techniques for likelihoods, and Sequential Monte Carlo methods. Although these methods have been and are highly successful in making likelihood-based inference accessible to a wide range of problems from virtually every area of science and technology, we now have a far better understanding of their limitations, for example in high-dimensional problems and for massive data sets. Thus many challenging statistical inference problems of the 21st century cannot be addressed using existing likelihood-based methods. Examples which motivate the current project come from genetics, genomics, infectious disease epidemiology, ecology, commerce, and bibliometrics. However there have been various recent breakthroughs in computational and statistical approaches to intractable likelihood problems, including pseudo-marginal and particle MCMC, likelihood-free methods such as Approximate Bayesian Computation, composite and pseudo-likelihoods, new simulation methods for hitherto intractable stochastic models, and adaptive Monte Carlo methods. These advances coupled with developments in multi-core computational technologies such as GPUs, have enormous potential for extending likelihood methods to meet the most difficult challenges of modern scientific questions. ongoing shared links with nodes of i-like grant, also new links and attraction of new talent to the institution. |
Year(s) Of Engagement Activity | 2015 |
URL | http://www.sustain.bris.ac.uk/ws-ilike/#overview |
Description | The Fidelity of Dynamic Signaling by Noisy Biomolecular Networks |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Participants in your research and patient groups |
Results and Impact | Conference Presentations The Fidelity of Dynamic Signaling by Noisy Biomolecular Networks, MASAMB 2013 (Mathematical and Statistical Aspects of Molecular Biology) |
Year(s) Of Engagement Activity | 2013 |
URL | http://www.theosysbio.bio.ic.ac.uk/masamb/index.html |
Description | UK-Causal Inference Meeting 2015 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Participants in your research and patient groups |
Results and Impact | UK-CIM is an initiative to organise a regular UK based meeting on causal inference as a collaborative effort across the methodology research community in the health, economics and social sciences. UK-CIM aims to: Provide forum for people interested in causal inference to meet informally Provide a forum for early career researchers to highlight their work Offer opportunities for networking to foster future research opportunities and collaborations Please note that registration for the meeting is not restricted to people from the UK, and we welcome participation from anyone who would like to attend. The theme of the meeting is "Causal Inference in Health, Economic and Social Sciences". Causal inference is broadly defined, and the focus is on methodology and challenging applications, though presentations relating to interesting applications that highlight necessary methodological extensions are also encouraged. |
Year(s) Of Engagement Activity | 2015 |
URL | http://www.sustain.bris.ac.uk/ws-uk-cim/ |
Description | World Conference of the International Society for Bayesian Analysis |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | World Conference of the International Society for Bayesian Analysis (ISBA), Kyoto, Japan (2012) Graphical Model Selection over Huge Profile Partition Spaces with Dependent Clusters |
Year(s) Of Engagement Activity | 2012 |