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Homepage of Piet Groeneboom

TUDelft/DIAM
Van Mourik Broekmanweg 6
2628 XE Delft
E-mail: P.Groeneboom AT tudelft.nl

Professor
Prof. dr. P. Groeneboom

Personal

Emeritus professor of Statistics at the Faculty EWI (Electrical Engineering, Mathematics and Computer Science) of the University of Technology, Delft.
Member of DIAM (Delft Institute of Applied Mathematics) at Delft University.

Book with co-author Geurt Jongbloed (published December, 2014), see: Nonparametric Estimation under Shape Constraints
Review of the book in Mathematical Reviews of MathSciNet of the American Mathematical Society: review.
Annotations and corrections for the book are listed in Annotations for book.

The second part of my book "Information Bounds and Nonparametric Maximum Likelihood Estimation" (Birkhäuser, 1992) with co-author Jon Wellner is based on summer lectures I gave in Stanford in 1990.
The Stanford lectures are given here: Stanford lectures.

Oberwolfach lecture on the single index model (January, 2020)

Interview, Statistical Science, Volume 34, Number 1, 2019.

I have Erdös number 3, but more importantly (for me) Heifetz number 2 (I owe the latter observation to Marloes Maathuis).

Blogs, started during the attempts to get Lucia de Berk out of jail: Piet Groeneboom's blog

R script for confidence intervals, based on the Grenander estimator

R scripts for the Cox model with interval censored data

R scripts for estimation methods in the single index model

R script for the primal-dual interior point algorithm for computing the real MLE in the survival-sacrifice model

A lecture on the work of Orlitsky and his collaborators on extrapolation matters: How many words did Shakespeare know?
The result of my implementation of the Metropolis Hastings algorithm here, combined with stochastic EM, were used in lectures of Richard Gill.

On August 6 and 7, 2013, I delivered the Wald lectures at the Joint Statistical Meeting in Montreal:
Wald lecture 1
Wald lecture 2
A description of the content of these lectures can be found in the IMS bulletin: Wald Lectures