World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
48
Citations
13404
World Ranking
1188
National Ranking
30

Overview

Anthony N. Pettitt is affiliated with the Queensland University of Technology in Australia. Their research spans several interdisciplinary fields, predominantly Biochemistry, Genetics and Molecular Biology, Mathematics, and Computer Science.

The scientist's key areas of study include Molecular Biology, Genetics, Statistics and Probability, Artificial Intelligence, and Modeling and Simulation. Their work focuses on topics such as gene expression and cancer classification, genetic associations and epidemiology, bioinformatics and genomic networks, genetic and phenotypic traits in livestock, Markov chains and Monte Carlo methods, Gaussian processes and Bayesian inference, and statistical methods with Bayesian inference.

Anthony N. Pettitt has contributed to several publications in notable venues. These include:

  • Bayesian meta-analysis models for cross cancer genomic investigation of pleiotropic effects using group structure (2020), published in Statistics in Medicine
  • Comparisons of statistical distributions for cluster sizes in a developing pandemic (2022), published in BMC Medical Research Methodology
  • Using a Supervised Principal Components Analysis for Variable Selection in High-Dimensional Datasets Reduces False Discovery Rates (2025), published in Statistics in Medicine
  • Using a supervised principal components analysis for variable selection in high-dimensional datasets reduces false discovery rates (2020), published in bioRxiv (Cold Spring Harbor Laboratory)
  • Analyse de la pléiotropie dans les GWAS à l'aide de méthodes bayésiennes prenant en compte la structure de groupe de variables (2021), published in Revue d Épidémiologie et de Santé Publique

Frequently collaborating with other researchers, Anthony N. Pettitt has worked alongside Kerrie Mengersen, Benoît Liquet, Taban Baghfalaki, Pierre-Emmanuel Sugier, and Thérèse Truong.

Their publications appear most often in journals such as Statistics in Medicine, BMC Medical Research Methodology, bioRxiv (Cold Spring Harbor Laboratory), Revue d'Épidémiologie et de Santé Publique, and arXiv (Cornell University).

Best Publications

  • A Non-Parametric Approach to the Change-Point Problem

    A. N. Pettitt

  • Importance Nested Sampling and the MultiNest Algorithm

    Farhan Feroz;Michael P. Hobson;Ewan Cameron;Anthony N. Pettitt

  • An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants

    Jesper Moller;Anthony N. Pettitt;Robert W. Reeves;Kasper K. Berthelsen

  • Marginal likelihood estimation via power posteriors

    Nial Friel;Anthony N. Pettitt

  • Model-based geostatistics. Discussion. Authors' reply

    P. J. Diggle;J. A. Tawn;R. A. Moyeed;R. Webster

  • A Review of Modern Computational Algorithms for Bayesian Optimal Design

    Elizabeth Gabrielle Ryan;Elizabeth Gabrielle Ryan;Christopher Drovandi;James McGree;Anthony Pettitt

  • A two-sample Anderson-Darling rank statistic

    A. N. Pettitt

  • Nonparametric Methods in General Linear Models.

    A. N. Pettitt;M. L. Puri;P. K. Sen

  • Estimation of parameters for macroparasite population evolution using approximate bayesian computation.

    C. C. Drovandi;A. N. Pettitt;A. N. Pettitt

  • A simple cumulative sum type statistic for the change-point problem with zero-one observations

    A. N. Pettitt

  • The Kolmogorov-Smirnov Goodness-of-Fit Statistic with Discrete and Grouped Data

    A. N. Pettitt;M. A. Stephens

  • Proportional Odds Models for Survival Data and Estimates Using Ranks

    A. N. Pettitt

  • Inference for the Linear Model Using a Likelihood Based on Ranks

    A. N. Pettitt

  • Modeling length of stay in hospital and other right skewed data: comparison of phase-type, gamma and log-normal distributions.

    Malcolm Faddy;Nicholas Graves;Nicholas Graves;Anthony Pettitt;Anthony Pettitt

  • A stochastic mathematical model of methicillin resistant Staphylococcus aureus transmission in an intensive care unit: predicting the impact of interventions.

    E.S. McBryde;A.N. Pettitt;D.L.S. McElwain

  • Modified Cramér-von Mises statistics for censored data

    A. N. Pettitt;M. A. Stephens

  • Approximate Bayesian Computation for astronomical model analysis: a case study in galaxy demographics and morphological transformation at high redshift

    E. Cameron;A. N. Pettitt

  • Sampling Designs for Estimating Spatial Variance Components

    A. N. Pettitt;A. B. Mcbratney

  • Approximate Bayesian computation using indirect inference

    Christopher C. Drovandi;Anthony N. Pettitt;Malcolm J. Faddy

  • Likelihood-free Bayesian estimation of multivariate quantile distributions

    Christopher C. Drovandi;Anthony N. Pettitt

  • Model-based geostatistics - Discussion

    Roberta Webster;Andrew Lawson;C Glasbey;G Horgan

  • Wiley Series in Probability and Statistics

    Clair L. Alston;Kerrie L. Mengersen;Anthony N. Pettitt

Frequent Co-Authors

Kerrie Mengersen
Kerrie Mengersen Queensland University of Technology
Andry Rakotonirainy
Andry Rakotonirainy Queensland University of Technology
Mark C. Bellingham
Mark C. Bellingham University of Queensland
Nicholas Graves
Nicholas Graves Queensland University of Technology
Ian Turner
Ian Turner Queensland University of Technology
D. M. Titterington
D. M. Titterington University of Glasgow
David Wilson
David Wilson Burnet Institute
Archie C. A. Clements
Archie C. A. Clements Queen's University Belfast
Michael A. Stephens
Michael A. Stephens Simon Fraser University
Sukumar Chakraborty
Sukumar Chakraborty Commonwealth Scientific and Industrial Research Organisation

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

For those studying Mathematics in the USA, expanding skills through related online degrees can open diverse career opportunities. Many students consider advancing into business by pursuing an online MBA with transfer credits accepted. This pathway allows learners to leverage their prior academic credits, making it more efficient and cost-effective to transition into management roles.

With the increasing demand for data-driven decision making, a data analytics master’s degree is becoming a popular choice. It complements mathematical foundations by focusing on data interpretation and computational skills, ideal for careers in technology, finance, and research.

For professionals looking for flexibility or a quicker entry into business education, exploring what MBA programs can I get into helps identify options that cater to various academic backgrounds and admission requirements.

Similarly, if convenience and accessibility are priorities, understanding the easiest MBA online programs can guide students toward degrees that accommodate busy schedules without compromising quality education.

Best Scientists Citing Anthony N. Pettitt

Trending Scientists

Recently Published Articles