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Much ado about nothing: a review of the state of the art of incomplete data Professor Rosemary Bailey EXPERIMENTS IN RECTANGULAR AREAS: RESTRICTED RANDOMIZATION OF ROW-COLUMN DESIGNS Professor Ray Chambers
Maximum Likelihood under Informative Sampling Dr David Scott The Hyperbolic and Related Distributions Dr Russell Millar ASSESSMENT OF HIERARCHICAL MODELS FOR COUNT DATA Dr Rolf Turner Direct Maximization of the Likelihood of a Hidden Markov Model Dr Murray Jorgensen
Where have all the Young Men gone? Professor Bruce Weir
THE BIRTHDAY PROBLEM and DNA PROFILES Professor William J Reed
Normal-Laplace Distributions and their Applications Hadley Wickham Interactive Graphics John Leathwick (NIWA) and Jane Elith (University of Melbourne) Boosted Regression Trees - a major advance in statistical modelling tools Dr Yong Wang Extending the Fisher scoring and Gauss-Newton methods for complex statistical optimisation problems Dr Thomas Yee A Framework for Regression Dr Murray Jorgensen The Development of Statistics in New Zealand Rohan Maheswaran A New Approach to Robust Estimation Dr Murthy Mittinty Nearest Neighbour Imputation Richard Penny Statistics New Zealand and the Official Statistics System - Data Collection and Access Dr James Curran A MCMC method for resolving two person DNA mixtures Dr Lyn Hunt Using multiple choice questions as an assessment device for statistical thinking Associate Professor David Whitaker The state of the art in the generation of efficient statistical designs Professor J A John Design, GenStat and CycDesigN Peter Mullins Using Excel for inspecting segments of a time series of reasonable length Dr Beatrix Jones Fitting and interpreting sparse Gaussian graphical models for high dimensional data Professor Chris Triggs Establishing Identity Dr Michael Stuart Mathematical thinking versus statistical thinking; redressing the balance in statistical teaching Dr Claire Jordan CART, PPM's and PBRF Professor George Styan Issai Schur (1875-1941) and the early development of the Schur complement, S–RP-1Q: photographs, documents and biographical remarks. Dr Daniel C. I. Walsh The Importance Sampling Hough Transform Jan Bulla Introduction to Hidden Markov Models Angelika van der Linde General measures of variability and dependence for multivariate continuous distributions. Professor Rosemary Bailey Hasse diagrams to describe the structure of designed experiments Professor Jacques Poot On the use of meta-analysis in economics Professor J A John Inverse of the Information Matrix Dr David Johnson Teaching Statistics with Microsoft Excel Professor Peter Davis Social facts and social stats: applications in quantitative sociology Dr James Curran Some issues surrounding the interpretation of Low Copy Number (LCN) DNA evidence. Dr Murray Jorgensen Estimating a density of microbial densities Harold V. Henderson Dynamic Graphics in Statistical Consulting Professor David M Ryan Robustness Issues in Aircrew Tours of Duty Optimisation Dr Ray Hoare Why do we need ANOTHER statistics program? Dr Colin Aitken Evaluation of Trace Evidence in the form
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Dr Michael Bulmer Virtual Worlds for Teaching Mathematics and Statistics Graham McBride Some Issues in Quantitative Health Risk Assessments for Waterborne Diseases Professor Chris Wild Regression Problems with Missing Data Megan Jowsey (Project Coordinator) and Rachel Cunliffe (Web site/Publicity Developer) CensusAtSchool NZ: a statistical experience for children Nicholas T Longford Stability of household income in European countries Dr Neil Cox What role does Excel have in the practice and teaching of statistics? Dr Lyn Hunt Unsupervised Learning from Incomplete Three-way Data using a Mixture Model Approach Dr James Curran Two Problems in Forensic Science Ian Westbrooke Meeting statistical needs in a conservation management organisation Emlyn Williams Statistical consulting and research in CSIRO Forestry and Forest Products Carole Wright Row-column Designs and their Contractions Dave Saville Multiple comparison procedures: consistency and family-size robustness Associate Professor David Whitaker Optimal Stratified Sampling Designs Hans Hockey Drug Development and Statistics Robert G. Easterling* Statistical Foundations for the Validation of Computer Models Professor Keith J Worsley Heritability random fields Dr Niall Broekhuizen Verification of an Individual-Based Model of the foraging of Southern Buller's Albatross by comparison with ship-board observations Bryan Manly The Assessment of Forestry on Northern Spotted Owls Dr Robert G. Newcombe Confidence Intervals for Proportions and Related Quantities Dr Martin Upsdell From Analysis of Means and Analysis of Coefficients to Analysis of Curves Dr Mik Black Statistical Issues in the Design and Analysis of Spotted Microarray Experiments Dr Marti J. Anderson Canonical analysis of principal coordinates: flexible constrained ordination Dr Jennifer Brown Designing an efficient adaptive cluster sample Dr Judi McWhirter Catching the Bayesian Wave: An MCMC Approach to Modelling Pulsatile Data Jock MacKay Some Issues in Variation Reduction Dr M A Jorgensen Using finite mixtures to robustify statistical models Associate Professor Stefan Steiner Seven Habits of Highly Effective Industrial Problem Solvers: An Overview of Statistical Engineering (Shanin Methods) Professor J A John Crossover Designs in Clinical Trials Associate Professor David Whitaker Integer Programming: Constraint formulation with binary variables Dr Anthony Lehmann GRASP: Generalized Regression Analysis and Spatial Prediction in Ecology Professor Alastair Scott Estimating Interviewer and Observer Effects for Binary Responses Professor Les Foulds Bookmobile Routing and Scheduling in Buskerud County, Norway Associate Professor Andy Philpott Optimisation in Electricity Pool Markets |
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Department of Statistics, University of Waikato 2002-08-15 GB.19 (G block basement, Room 19) In studies of the robustness of statistical estimators it has been common to use mixtures of distributions. Commonly a mixture of two distributions is used with one component modelling the good data and the other some contamination, although this could be extended to several different types of bad data.
It does not appear to be very common to have used the maximum likelihood estimator of the parameter vector of a particular mixture component as a robust estimator for a statistical model.
In this talk we explore this approach in the contexts of location/scale estimation and regression. We find that our proposed estimators have good influence properties and can sometimes work well even when there is more bad data than good.
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