Modern Spatial Statistics Conference –In honour of Julian Besag FRS

When: 11th and 12th May 2011

Where:

11th May, Gibson Room, Level 10, Z Block
12th May, Owen J Wordsworth, Room Level 12, S Block

QUT Gardens Point, Brisbane, Queensland, Australia

Cost: The conference is free.

Registration: Conference attendees are required to register. To register send details of: your title, full name, institution or company name, to modess11@qut.edu.au
eg. Professor Jane Smith, Queensland University of Technology

Location: http://www.qut.edu.au/about/location/

Maps: http://www.qut.edu.au/about/location/pdf/gp_10_2010_colour_map.pdf

About the Conference

Spatial statistics is a branch of statistical science dealing with the analysis of spatial data.- any data that are attributed to spatial locations. The conference is in honour of Julian Besag a noted spatial statistician who is credited with some of the initial work and theories in this area of statistics who passed away in August last year.

The conference is to give local statisticians from diverse backgrounds an opportunity to hear of high profile speakers from the field of spatial statistics in an intensive two (2) day session. In particular, the conference will allow local students to hear and network with these world renowned researchers. This will be an interactive conference which involves group discussion sessions following each keynote speaker and the poster session, is intended to encourage collaboration between attendees.

About Julian Besag FRS

Peter Green states "Julian Besag's contributions to the discipline of statistics are profound, and have been, and continue to be, of far-reaching consequence." Besag was known as an independent and creative thinker and is often credit with the "fathering" modern spatial modelling.

The general area in which he made the biggest impression is the conditional modelling of spatial systems. Together with the parallel, independent, work on interaction in contingency tables by Darroch, Lauritzen and Speed, Julian Besag's work in the 70s and early 80s [especially the papers in JRSSB (1974), regarded as seminal, and JRSSB (1972) and The Statistician (1975)] laid the foundations for the entire contemporary tradition of highly structured stochastic systems. This strategy for building complex global models through local specifications guaranteed to be self-consistent has made a huge impact on stochastic modelling in many areas of science, medicine and technology, and stimulated important work on statistical inference for such systems, and on their probabilistic theory.

What began in his early work as a quest for flexible and mathematically-sound models for ecological phenomena, resulting in the notion of modelling spatial systems as Markov random fields led on directly to the idea of MRFs as a generic model for interacting systems, with Julian himself responsible for adapting the models and the methodology to agricultural field trials, archaeological problems, image analysis and disease mapping, and to hierarchical versions of such models under the Bayesian paradigm.

The second major plank to the methodological side of his research was the innovatory work on inferential methods for spatial systems, and their computational implementation. Especially noteworthy are the notion of pseudolikelihood in interacting systems [papers in The Statistician (1975) and Bulletin ISI (1978)], as a computationally tractable alternative to the true likelihood, the 'iterated conditional modes' algorithm [JRSSB (1986)], important contributions to the algebra of interacting systems [JRSSB (1981), Biometrika (1995), Biometrika (2002)] and his role as one of the very early proponents of Markov chain Monte Carlo methods for fitting statistical models [JRSSB (1986), J Appl Stat (1989), Ann Inst Stat Math (1991), JRSSB (1993), Stat Sci (1995)]. In particular, he was well ahead of his time in recognising the duality between the conditional specification of stochastic models and the construction of algorithms for such models using these conditional specifications.

The applications areas in which Julian Besag worked were not simply sources of convenient illustrative examples. In field trials [Biometrics (1986), Stat Sci (1995), JRSSB (1999)], spatial epidemiology [JRSSA (1991), Ann Inst Stat Math (1991)] and image analysis [JRSSB (1986), J Appl Stat (1989), Scand J Stat (1988)], he made substantive contributions, based on perceptive understanding of the subject matter involved, and a clearly articulated and often rather subtle view of both the role and the limitations of statistical modelling in the context. The impact he has had on these and other fields is indicated by the high rate of citation of his work in relevant subject journals.

Among the main strengths of his current department, Julian cites the wide range of research interests and the recruitment of excellent junior faculty and graduate students.

Julian coauthored two further read papers to RSS in 1993 and 1999, the first on MCMC methodology with Peter Green, the second on Bayesian analysis of agricultural field experiments with David Higdon. Among other topics, Julian continues to work on exact Monte Carlo and MCMC p-values, stimulated originally by Brian Ripley. Julian first wrote about the former in 1977 with Peter Diggle, who had been a student at Liverpool, and introduced the latter in a 1989 Biometrika paper with Peter Clifford.

Julian is a past member of council of RSS and was elected Member of the International Statistical Institute in 1984 and Fellow of IMS in 1991. He co-chaired the panel that wrote the wide-ranging report on "Spatial Statistics and Digital Image Analysis'', published by NAS in 1991, and gave an IMS special invited presentation in 1992. His research has been cited in more than 250 different journals.

Keynote Speakers

Professor Chris Glasbey

International speaker Professor Chris Glasbey is currently lives and works in Scotland. In 2009 was elected to Fellowship of The Royal Society of Edinburgh. Chris Glasbey's area of research is spatial and temporal models, including image analysis and bioinformatic applications. I coordinate BioSS's PhD programme and hold honorary/visiting professorships at Heriot-Watt and Edinburgh Universities, SAC and Queensland University of Technology, Australia.

For more information about Professor Glasbey please visit:
http://www.bioss.ac.uk/staff/chris.html

Professor Adrian Baddeley

Professor Adrian Baddeley is a statistician with interests in spatial and geometric problems. His recent work is focused on the statistical analysis of spatial point patterns, including theory, methodology, software and real applications. He was chair of Statistics at the University of Western Australia from 1994 to 2010 and is now a research scientist with CSIRO Mathematical and Information Sciences. Professor Baddeley is a Fellow of the Australian Academy of Science and a winner of the Hannan and Pitman Medals for statistics.

Dr Erin Peterson

Erin Peterson is a research scientist with the CSIRO Division of Mathematics, Informatics and Statistics in Brisbane, Australia. She is a spatial ecologist working on a variety of projects relating to freshwater monitoring and modelling, primarily within the Water for a Healthy Country Flagship. Her background and experience allow her to work at the interface of geospatial science, aquatic ecology, landscape ecology, and environmental statistics. She has a keen interest in tool development, which helps to ensure that the methodologies she develops are made accessible to ecologists and natural resource managers.

For more information about Dr Peterson please visit:
http://www.csiro.au/people/Erin.Peterson.html

Professor Kerrie Mengersen

Kerrie is a world leader in statistics who has closely collaborated with Julian. Their highly cited joint paper:

BESAG, J., GREEN, P., HIGDON, D., MENGERSEN, K. (1995) Bayesian computation and stochastic systems. Statist. Science 10, 366, is a modern classic in the Bayesian scene.

Kerrie's current research interests include:

Bayesian learning: theory, methods, computation and application: Mixture models; meta-analysis; Bayesian networks; image classification and spatio-temporal modelling; MCMC and associated algorithms; prior representation; elicitation of expert information.

Statistical modelling in industry, environment and health: World Health Organisation project on indoor air quality and health in Lao PDR; integrating diverse sources of information in Bayesian models for improved medical and public health practice; Bayesian models for high throughput genetic genomics; Bayesian networks for analysis of algal blooms in Qld and cheetah survival in southern Africa.

Statistical methods for biosecurity: Modelling; prediction; sampling; uncertainty modelling and analysis.

For more information about Professor Mengersen please visit: http://staff.qut.edu.au/staff/mengerse/

Professor Dani Gamerman

Dani's current research interests include dynamic models, spatial statistics, survival analysis, stochastic simulation, econometrics and Bayesian inference. Dani is a visiting lecturer in (USP, IMPA and UFPE) in Brazil and abroad (London, Rome, Madrid, Milan, Vienna, Connecticut and Duke) and colaborador honor�fico of Universidade Rey Juan Carlos in Madrid. Author of the books Monte Carlo Markov Chain: Stochastic Simulation for Bayesian Inference, published by Chapman and Hall in 1997 (1st. edition) and 2006 (2nd. edition, com Hedibert F. Lopes) and Statistical Inference: an Integrated Approach (with Helio S. Migon), published by Arnold in 1999. He has many papers published in many A* statistical journals including Journal of the Royal Statistical Society, Series B, Biometrika, Applied Statistics and Journal of Multivariate Analysis.

For more information about Professor Gamerman please visit: http://acd.ufrj.br/~dani/index.htm

Professor Tony Pettitt

Professor Tony Pettitt is an internationally renowned statistician, with particular specialist skills in the areas of Bayesian analysis and computation. He has experience in work associated with spatial statistics such as CAR models, efficient calculations for intractable normalising constants and continuous Gaussian random field modelling.

For more information about Professor Tony Pettitt please visit: http://staff.qut.edu.au/staff/pettitt/

Conference Program

Tuesday, 10^th May	CRC SI for Spatial Information S Block Room S405
	1:00-1:15	Introduction
	1:15-2:00	Stephen Ball and Peter Jacoby
	2:00-2:30	Discussion
	2:30-3:00	Break
	3:00-3:45	Susanna Cramb
	3:45-4:15	Discussion
	4:15-4:45	Breakout Groups
	4:45-5:00	Close of Workshop
Wednesday, 11^th May	Modern Spatial Statistics Conference (Gibson Room Level 10, Z Block)
	9:00 - 10:00	Keynote Speaker 1	Professor Dani Gamerman
	10:00 - 10:30	Contributed Session 1	Dr. David Clifford
	10:30 - 11:00	Morning Tea
	11:00-11:30	Contributed Session 2	Matt Falk
	11:30-12:00	Contributed Session 3	Dr.Gopalan Nair
	12:00 - 1:30	Lunch (not provided) and Poster Session
	13:30 - 14:30	Keynote Speaker 2	Professor Adrian Baddley
	14:30 - 15:00	Contributed Session 4	Dr. Chris Strickland
	15:00 - 15:30	Afternoon Tea
	15:30 - 16:30	Keynote Speaker 3	Professor Tony Pettitt

	18:00-22:00	Welcome Dinner at Era Bistro
Thursday, 12^th May	Owen J Wordsworth, Room Level 12, S Block
	9:00 - 10:00	Keynote Speaker 4	Professor Chris Glasbey
	10:00-10:30	Contributed Session 5	Margaret Donald
	10:30-11:00	Morning Tea
	11:00-12:00	Contributed Session 6	Dr.Clare McGrory
	12:00-13:00	Lunch (not provided)
	13:00 - 14:00	Keynote Speaker 5	Dr Erin Petersen
	14:00 - 14:30	Contribution Session 7	Dr. Samantha Low Choy
	14:30 - 15:00	Contributed Session 8	Dr. Clair Alston
	15:00 - 15:30	Afternoon Tea
	15:30 - 16:30	Keynote Speaker 6	Professor Kerrie Mengersen
	16:30 - 16:45	Close of Conference

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Organising Committee

Professor Kerrie Mengersen (Co-Chair)
Dr Claire Alston (Co-Chair)
Dow Jaemjaret

For further information please contact Dow Jaemjaret at dow.jaemjamrat@qut.edu.au or telephone +61 7 3138 2063