Dr Ben O'Neill

BActuarial (Hons), LLB, LLM, MEc, PhD (Statistics) (ANU)
Research Fellow
ANU College of Health and Medicine

Areas of expertise

  • Applied Statistics 010401
  • Statistics 0104
  • Biostatistics 010402
  • Statistical Theory 010405
  • Probability Theory 010404

Research interests

  • Sampling theory and experimental design;
  • Applied statistical modelling;
  • Statistical prediction and machine learning;
  • Bayesian theory and applied Bayesian statistics.

Biography

Ben is a statistician and data scientist in NCEPH.  He is interested in statistical methodology and theory, and applied statistical analysis.  His main area of research is sampling theory and prediction problems, and he is also interested in statistical programming and applied data analysis in R.  In his role at NCEPH, Ben collaborates with other researchers on research projects relating to population health, and he provides statistical advice relating to survey and experimental design, collection and analysis of data, statistical modelling, graphical presentation of results, and reproducible data analysis.

 

Ben has a broad range of academic interests including mathematics, statistics, economics, philosophy and law.  Prior to joining ANU he worked as Lecturer in Statistics at UNSW, and he has also undertaken various statistical consulting roles in industry and government.  He has previously practiced as a lawyer.

Researcher's projects

  • Statistical discrimination in sequential binary decision-processes;
  • Discrimination and methodological approaches in social decision processes;
  • Regression modelling with the generalised error distribution;
  • Non-parametric regression using kernel residual distributions;
  • Geometric analysis of linear regression;
  • Sample-size determination from pilot surveys;
  • Asymptotic properties of point-based predictors.

Available student projects

  • Statistical modelling of queueing and resource parity across groups;
  • Acceptance-rejection games with discounting;
  • Stationary constrained Gaussian processes.

Publications

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Updated:  25 April 2019 / Responsible Officer:  Director (Research Services Division) / Page Contact:  Researchers