World's Best Scientists 2026 revealed!

Research.com Recognitions

  • 2020 - Fellow of the Australian Academy of Science
  • 2018 - Fellow of the American Statistical Association (ASA)

Overview

Aurore Delaigle is a researcher affiliated with the University of Melbourne in Australia. Their work primarily spans the field of Computer Science, with a strong focus on Statistics and Probability as well as Artificial Intelligence, Infectious Diseases, Epidemiology, and Environmental Engineering.

The main topics covered in their research include Statistical Methods and Inference, Bayesian Methods and Mixture Models, SARS-CoV-2 detection and testing, Soil Geostatistics and Mapping, Nutritional Studies and Diet, Fatty Acid Research and Health, and Data-Driven Disease Surveillance.

Aurore Delaigle has published papers in multiple respected journals. Some recent papers include:

  • Estimating the Covariance of Fragmented and Other Related Types of Functional Data (2020), Journal of the American Statistical Association
  • Semiparametric Estimation of the Distribution of Episodically Consumed Foods Measured With Error (2020), Journal of the American Statistical Association
  • Group Testing Regression Analysis with Covariates and Specimens Subject to Missingness (2023), Statistics in Medicine
  • Group Testing Regression Analysis with Missing Data and Imperfect Tests (2022), Statistica Sinica
  • Nonparametric density estimation for intentionally corrupted functional data (2020), Statistica Sinica

Their frequent publication venues include the Journal of the Royal Statistical Society Series B (Statistical Methodology), Journal of the American Statistical Association, Statistica Sinica, Statistics in Medicine, and Oberwolfach Reports.

Their regular collaborators include Steffen L. Lauritzen, Félix Camirand Lemyre, Ruoxu Tan, Alexander Meister, and S. Wood.

Aurore Delaigle has been recognized with awards such as Fellow of the American Statistical Association in 2018 and Fellow of the Australian Academy of Science in 2020.

Best Publications

  • Practical bandwidth selection in deconvolution kernel density estimation

    Aurore Delaigle;Irène Gijbels

  • On deconvolution with repeated measurements

    Aurore Delaigle;Peter Hall;Alexander Meister

  • Achieving near perfect classification for functional data

    Aurore Delaigle;Peter Hall

  • Defining probability density for a distribution of random functions

    Aurore Delaigle;Peter Hall

  • Bootstrap bandwidth selection in kernel density estimation from a contaminated sample

    A Delaigle;Irène Gijbels

  • Methodology and theory for partial least squares applied to functional data

    Aurore Delaigle;Peter Hall

  • A Design-Adaptive Local Polynomial Estimator for the Errors-in-Variables Problem.

    Aurore Delaigle;Jianqing Fan;Raymond J. Carroll

  • Estimation of integrated squared density derivatives from a contaminated sample

    Aurore Delaigle;Irène Gijbels

  • Density estimation with heteroscedastic error

    Aurore Delaigle;Alexander Meister

  • Componentwise classification and clustering of functional data

    A. Delaigle;P. Hall;N. Bathia

  • Classification Using Censored Functional Data

    Aurore Delaigle;Peter Hall

  • Using SIMEX for Smoothing-Parameter Choice in Errors-in-Variables Problems

    Aurore Delaigle;Peter Hall

  • Robustness and accuracy of methods for high dimensional data analysis based on Student's t‐statistic

    Aurore Delaigle;Peter Hall;Jiashun Jin

  • Nonparametric Regression Estimation in the Heteroscedastic Errors-in-Variables Problem

    Aurore Delaigle;Alexander Meister

  • Nonparametric Prediction in Measurement Error Models.

    Raymond J. Carroll;Aurore Delaigle;Peter Hall

  • Non-parametric regression estimation from data contaminated by a mixture of Berkson and classical errors.

    Raymond J. Carroll;Aurore Delaigle;Peter Hall

  • Estimation of boundary and discontinuity points in deconvolution problems

    A Delaigle;Irène Gijbels

  • An alternative view of the deconvolution problem

    Aurore Delaigle

  • Nonparametric covariate-adjusted regression

    Aurore Delaigle;Peter Hall;Wen-Xin Zhou

  • USING SIMEX FOR SMOOTHING-PARAMETER CHOICE IN ERRORS-IN-VARIABLES PROBLEMS: technical details.

    Aurore Delaigle;Peter Hall

Frequent Co-Authors

Peter A. Hall
Peter A. Hall Harvard University
Raymond J. Carroll
Raymond J. Carroll Texas A&M University
Hans-Georg Müller
Hans-Georg Müller University of California, Davis
Song Xi Chen
Song Xi Chen Peking University
Jianqing Fan
Jianqing Fan Princeton University
Alois Kneip
Alois Kneip University of Bonn
Matt P. Wand
Matt P. Wand University of Technology Sydney
Larry Wasserman
Larry Wasserman Carnegie Mellon University

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