Australian Statistical Conference 2010 Fremantle, WESTERN AUSTRALIA Including OZCOTS 2010 - the 7Th Australian Conference on Teaching Statistics

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Australian Statistical Conference 2010 Fremantle, WESTERN AUSTRALIA Including OZCOTS 2010 - the 7Th Australian Conference on Teaching Statistics ASC 2010 Conference - Abstracts ABSTRACTS: 20th Australian Statistical Conference 2010 Fremantle, WESTERN AUSTRALIA including OZCOTS 2010 - The 7th Australian Conference on Teaching Statistics Abstracts of the ASC presentations are included by alphabetical / presenting author. Abstracts for Invited Speakers commence on page 31. Abstracts for Concurrent Sessions commence on page 45. Abstracts for Posters commence on page 259. Abstracts of the OZCOTS presentations are included in program order from page 287. An Author Index commences on page 313. ASC 2010 SCIENTIFIC PROGRAM COMMITTEE Ray Chambers (University of Wollongong) Brenton Clarke (Murdoch University) Chair Ross Darnell (CSIRO) John Henstridge (Data Analysis Australia) Deputy Chair Charles Pearce (Adelaide University) Katia Stefanova (Department of Agriculture and Food, WA) Paul Sutcliffe (Australian Bureau of Statistics) Alan Welsh (Australian National University) Frank Yu (Australian Bureau of Statistics) The ASC Abstracts were reviewed and edited by Brenton R Clarke with assistance from the following people: Russell John, Anna Munday, Katia Stefanova, Jane Speijers Ross Taplin, Berwin Turlach, Nihal Yatawara and Frank Yu. page | 29 December 2010 FREMANTLE, Western Australia page | 30 ASC 2010 Conference - Abstracts CRISP REVISITED: EFFECTIVENESS AND EFFICIENCY IN AUSTRALIAN OFFICIAL STATISTICS Geoff Allen, AM Allen Consulting Group Level 9, 60 Collins Street, Melbourne, Victoria [email protected] The 1974 (Crisp) Committee on Integration of Data Systems in Australian government concluded that there was serious sub-optimisation of the statistical efforts across departments and levels of government, inefficient use of the scarce statistical expertise available to the official statistics community, fragmentation, duplication and incompatibility of decentralised uncoordinated statistical collections and unnecessary response burdens on providers of data. It also noted an inadequate use across government of administrative data due to a lack of standardisation across agencies and a lack of data integration. This was seen to limit the value of available data for policy making, as well as being wasteful of financial and human resources. Significant administrative and policy changes were introduced to address these concerns. A current assessment is offered suggesting that many of these deficiencies continue to exist or have re-emerged with a consequent sub-optimisation of evidence based decision making and inefficient use of scarce expertise and financial resources. While technical advances are facilitating improvements, the complexities of modern government are making co-ordination and data integration more difficult. However new demand is being felt for data collection and analysis in areas such as social inclusion, environment including impacts of climate change policies, and infrastructure, which will keep pressure on scarce government resources and threaten to increase ad hoc and suboptimal statistical initiatives in agencies. Some directions for the way ahead are made. Geoff Allen, AM, was senior advisor to the Federal Treasurer and Leader of the Opposition, business school academic and co-founder and foundation CEO of the Business Council of Australia. He is founder and is currently Director of the Allen Consulting Group. He has been Chairman of a number of State and Commonwealth Government advisory councils including the Australian Government's Trade Policy Advisory Council and director of a number of public companies. He is currently Chairman of the Australian Statistics Advisory Council, National Chairman of the Committee for Economic Development of Australia (CEDA) and Chairman of the Australasian Centre for Corporate Public Affairs. page | 31 December 2010 FREMANTLE, Western Australia NEW METHODOLOGY FOR SPATIAL POINT PATTERNS WITH GEOLOGICAL, ENVIRONMENTAL AND ASTRONOMICAL APPLICATIONS Adrian Baddeley CSIRO, CMIS, Leeuwin Centre 65 Brockway Rd, Floreat, WA 6014 [email protected] The statistical analysis of spatial patterns of points has long been an important problem in astronomy, ecology and geology. This talk describes new statistical methodology for spatial point process models, and recent applications to the analysis of large point pattern datasets in these three areas. This work is a collaboration between CSIRO, The University of Western Australia, and Aalborg University. We have developed analogues, for spatial point process models, of the classical techniques for model validation in (generalized) linear models such as residuals, leverage, influence measures, partial residual plots, added variable and constructed variable plots. We report an application to ecological surveillance of in Western Australian native woodland, on a scale involving millions of trees. Classical methods for spatial point pattern analysis are based on empirical functional summary statistics such as the K-function and the two-point correlation function. We have developed a general approach, based on the score test, which extends these techniques to non-stationary processes, using a counterpart of the one-dimensional point process compensator. In Geographical Information Systems (GIS), spatial point pattern data are often analysed by discretising space and applying logistic regression. It is not widely understood that this is equivalent to assuming a loglinear Poisson point process model. Benefits of this insight include better parameter estimation and more informative prediction. We demonstrate an application to prospective geology in Western Australia. Adrian Baddeley is one of Australia’s leading statisticians. He is a winner of the Pitman Medal, Hannan Medal, and Australian Mathematical Society Medal, and is a Fellow of the Australian Academy of Science. He has held positions at Trinity College Cambridge, The University of Bath, CSIRO, the Centre for Mathematics and Computer Science in Amsterdam, and the University of Leiden in The Netherlands. Until recently he was Professor of Statistics at the University of Western Australia. He is now a Science Fellow with the CSIRO Division of Mathematics, Informatics and Statistics (CMIS) based at Floreat, Western Australia. page | 32 ASC 2010 Conference - Abstracts STATISTICAL INFERENCE BASED ON FRÉCHET DIFFERENTIABILITY AND APPLICATIONS Tadeusz Bednarski Economics Institute, University of Wroclaw, Poland ul. Uniwersytecka 22/26, 50-145 Wroclaw, Poland [email protected] A key step in building the inference procedures for statistical models is in providing distributional properties of statistics. The task may become complex when estimates are given implicitly as it is so frequently with robust procedures. The method of Fréchet differentiability is then a reliable and relatively simple tool in deriving approximate distributions of estimators. An estimator depending on the empirical distribution function which is Fréchet differentiable is also robust in a qualitative sense – its influence function is bounded and smooth. Even though the differentiability does not provide efficiency, in conjunction with a general idea of smooth trimming of the likelihood ratio, it may lead to very reasonable robust procedures in nonstandard and complex inferential situations. The aim of the lecture is to demonstrate that indeed the above general idea can be implemented usefully in practice. A differentiable modification of the partial likelihood estimator for the Cox model and a robust modification of the maximum likelihood estimator for the generalized Poisson model will be discussed and supplemented by real data examples (Bednarski (1993, 1996, 2004)). New results concerning the unit root testing in the time series will also be given to demonstrate potential use of the differentiability notion in statistical inference for stationary processes. References Bednarski, T. (1993). Robust estimation in Cox‘s regression model. Scandinavian Journal of Statistics. Vol. 20, pp 213-225. Bednarski, T., Zontek, S. (1996). Robust estimation of parameters in a mixed unbalanced model. Annals of Statistics. Vol. 24, pp 1493-1510. Bednarski, T. (2004). Robust estimation in the generalized Poisson model. Statistics, Vol. 38, pp 149- 159 Tadeusz Bednarski currently works at Economics Department of the University of Wroclaw as Head of Statistics Section. His main research interests are in asymptotic robust methodology, in particular in applications of the Fréchet differentiability to statistical inference in Poisson, Cox and time series models. From the practical standpoint his interests concern longitudinal studies of clinical data, insurance statistics, unemployment statistical studies, and econometric modelling in time series. page | 33 December 2010 FREMANTLE, Western Australia PLANNING FOR HEALTH Dr Jim Codde A/Executive Director, Service Planning and Development, South Metropolitan Area Health Service Western Australian Department of Health [email protected] The population of Western Australia has grown from 1.90 million in 2001 to 2.27 million in December 2009, with an annual rate of growth increasing from 1.4% to 3.1% over the same period, making WA‘s population the fastest growing in Australia. But what does all this mean for the planning of public health services? Does the fact that overseas migration accounts for almost two-thirds of this growth impact on the health needs of our population? Despite the minerals led economic boom in the northwest of WA, how do we ensure the health infrastructure plans account for the fact that
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