Adrian Baddeley

Adrian Baddeley (born 1955, Melbourne, Australia) is a statistical scientist working in the fields of spatial statistics,[1] statistical computing, stereology[2] and stochastic geometry.

Adrian Baddeley
Born1955
Melbourne, Australia
CitizenshipAustralian
Awards
Scientific career
FieldsStatistics
WebsiteCurtin University Staff Page

Life and career

Adrian Baddeley was educated at Eltham High School in Melbourne, Australia, and studied mathematics and statistics at the Australian National University (honours supervisor: Roger Miles) and the University of Cambridge (PhD supervisor: David George Kendall). He was elected a Junior Research Fellow at Trinity College Cambridge in the second year of his PhD. Subsequently he worked for the University of Bath (1982–85), the CSIRO Division of Mathematics and Statistics, Sydney (1985–88), the Centrum Wiskunde & Informatica, Amsterdam, The Netherlands (1988–94), the University of Western Australia (where he was Professor of Statistics from 1994 to 2010), CSIRO Division of Mathematics, Informatics and Statistics, Perth (2010-2012), and the Centre for Exploration Targeting at the University of Western Australia (2013-2014). He is now Professor of Computational Statistics at Curtin University.

Research

Stereology

Classical methods of stereology were limited by the requirement that the cutting plane be randomly oriented. Baddeley developed an alternative technique [3] in which the cutting plane is `vertical' (parallel to a fixed axis, or perpendicular to a fixed surface) making it possible to apply quantitative microscopy to cylindrical core samples, samples of flat materials, and longitudinal sections.

Baddeley is a leading advocate of statistical ideas in stereology. With Cruz-Orive he demonstrated the role of the Horvitz-Thompson weighting principle and the Rao-Blackwell theorem in stereological sampling.[2]

Spatial statistics

Baddeley has developed statistical methodology for analysing spatial patterns of points, including methods based on survival analysis, [4] nonparametrics, [5] [6] new point process models, [7] [8] model-fitting principles and algorithms [9] [10] [11] and open-source software. [12]

Honors and awards
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References
  1. A. Baddeley, E. Rubak and R.Turner, "Spatial Point Patterns: Methodology and Applications with R", Chapman and Hall/CRC Press 2015.
  2. A. Baddeley and E.B. Vedel Jensen, Stereology for Statisticians, Chapman and Hall/CRC Press 2005.
  3. A.J. Baddeley, H.J.G. Gundersen, and L.M. Cruz-Orive. Estimation of surface area from vertical sections. Journal of Microscopy, 142:259-276, 1986
  4. A.J. Baddeley and R.D. Gill, Kaplan-Meier estimators of interpoint distance distributions for spatial point processes. Annals of Statistics 25: 263-292, 1997.
  5. M.N.M. van Lieshout and A.J. Baddeley, A nonparametric measure of spatial interaction in point patterns. Statistica Neerlandica 50:344-361, 1996.
  6. A. Baddeley, J. Moller and R. Waagepetersen, Non- and semiparametric estimation of interaction in inhomogeneous point patterns, Statistica Neerlandica 54: 329-350, 2000.
  7. A.J. Baddeley and J. Moller, Nearest-neighbour Markov point processes and random sets. International Statistical Review 57:89-121, 1989.
  8. A.J. Baddeley and M.N.M. van Lieshout, Area-interaction point processes. Annals of the Institute of Statistical Mathematics 47:601-619, 1995.
  9. A. Baddeley and T.R. Turner, Practical maximum pseudolikelihood for spatial point patterns. Australian and New Zealand Journal of Statistics 42:283-322, 2000
  10. A. Baddeley, Time-invariance estimating equations. Bernoulli 6: 783-808, 2000.
  11. A. Baddeley, J.-F. Coeurjolly, E. Rubak and R. Waagepetersen, Logistic regression for spatial Gibbs point processes. Biometrika 101:377-392, 2014.
  12. A. Baddeley and R. Turner. Spatstat: an R package for analyzing spatial point patterns. Journal of Statistical Software 12(6):1-42, 2005. www.jstatsoft.org
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