World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
30
Citations
4806
World Ranking
3464
National Ranking
44

Research.com Recognitions

  • 2013 - Wald Memorial Lecturer

Overview

Piet Groeneboom is affiliated with the Delft University of Technology in the Netherlands. Their research primarily focuses on mathematics, with an emphasis on statistics and probability. The scientist's work covers a range of subfields including statistics and probability, artificial intelligence, global and planetary change, statistics, probability and uncertainty, and finance.

Their main topics of study include statistical methods and inference, Bayesian methods and mixture models, statistical methods and Bayesian inference, advanced statistical methods and models, statistical distribution estimation and applications, hydrology and drought analysis, and advanced statistical process monitoring.

Groeneboom has published extensively, with notable recent papers such as:

  • "Confidence intervals in monotone regression," 2024, Scandinavian Journal of Statistics
  • "Estimation of the incubation time distribution in the singly and doubly interval censored model," 2024, Statistica Neerlandica
  • "Confidence intervals in monotone regression," 2023, arXiv (Cornell University)
  • "Grenander functionals and Cauchy's formula," 2020, Scandinavian Journal of Statistics
  • "Estimation of the incubation time distribution for COVID-19," 2020, Statistica Neerlandica

Frequent publication venues for Groeneboom include:

  • arXiv (Cornell University)
  • Scandinavian Journal of Statistics
  • Statistica Neerlandica
  • Electronic Journal of Statistics

Among their frequent co-authors are Geurt Jongbloed and Fadoua Balabdaoui.

Groeneboom was recognized as a Wald Memorial Lecturer in 2013.

Best Publications

  • Information Bounds and Nonparametric Maximum Likelihood Estimation

    Piet Groeneboom;Jon A. Wellner

  • Brownian motion with a parabolic drift and airy functions

    Piet Groeneboom

  • Nonparametric Estimation under Shape Constraints

    Piet Groeneboom;Geurt Jongbloed

  • Estimating a monotone density

    P. Groeneboom

  • Estimation of a convex function: characterizations and asymptotic theory.

    Piet Groeneboom;Geurt Jongbloed;Jon A. Wellner

  • Large Deviation Theorems for Empirical Probability Measures

    P. Groeneboom;J. Oosterhoff;F. H. Ruymgaart

  • Computing Chernoff's Distribution

    Piet Groeneboom;Jon A Wellner

  • Nonparametric Estimation under Shape Constraints

    Piet Groeneboom;Geurt Jongbloed

  • Limit theorems for convex hulls

    Piet Groeneboom

  • The Concave Majorant of Brownian Motion

    Piet Groeneboom

  • The support reduction algorithm for computing non-parametric function estimates in mixture models

    Piet Groeneboom;Geurt Jongbloed;Jon A. Wellner

  • Lectures on inverse problems

    Piet Groeneboom

  • A canonical process for estimation of convex functions: the "invelope" of integrated Brownian motion + t4.

    Piet Groeneboom;Geurt Jongbloed;J. O. N. A. Wellner

  • Second class particles and cube root asymptotics for Hammersley's process

    Eric Cator;Piet Groeneboom

  • Asymptotically optimal estimation of smooth functionals for interval censoring, case 2

    Ronald Geskus;Piet Groeneboom

  • Kernel-type estimators for the extreme value index

    P. Groeneboom;H.P. Lopuhaä;P.P. de Wolf

  • Isotonic Estimation and Rates of Convergence in Wicksell's Problem

    Piet Groeneboom;Geurt Jongbloed

  • Limit theorems for functionals of convex hulls

    A. J. Cabo;P. Groeneboom

  • MAXIMUM SMOOTHED LIKELIHOOD ESTIMATION AND SMOOTHED MAXIMUM LIKELIHOOD ESTIMATION IN THE CURRENT STATUS MODEL

    Piet Groeneboom;Geurt Jongbloed;Birgit I. Witte

  • Bahadur efficiency and probabilities of large deviations

    P. Groeneboom;J. Oosterhoff

  • Current status data with competing risks: Consistency and rates of convergence of the MLE

    Piet Groeneboom;Marloes H. Maathuis;Jon A. Wellner

  • The suppport reduction algorithm for computing nonparametric function estimates in mixture models

    Piet Groeneboom;Geurt Jongbloed;Jon A. Wellner

  • A canonical process for estimation of convex functions: the "invelope" of integrated Brownian motion + t4.

    G. Jongbloed;P. Groeneboom;J.A. Wellner

Frequent Co-Authors

Jon A. Wellner
Jon A. Wellner University of Washington
Richard D. Gill
Richard D. Gill Leiden University

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