Piet Groeneboom

3.5k citations
63 papers · 1.9k indexed · 1 hit paper · h-index 22
Topics
Statistical Methods and Inference (36 papers)Bayesian Methods and Mixture Models (19 papers)Statistical Methods and Bayesian Inference (14 papers)

In The Last Decade

Piet Groeneboom

62 papers receiving 1.7k citations

Hit Papers

Information Bounds and Nonparametric Maximum Likelihood E...19922026200320141992100200300400

Peers

Piet Groeneboom
Comparison fields: 5 of 108
  • Statistics and Probability 1.5k
  • Artificial Intelligence 541
  • Mathematical Physics 229
  • Finance 224
  • Applied Mathematics 218
Replace Tailen Hsing with:
Tailen Hsing United States
Joel Zinn United States
Gordon Simons United States
Rolf–Dieter Reiss Germany
Yu. A. Rozanov Russia
Evarist Giné United States
Paul Deheuvels France
Galen R. Shorack United States
Ilya Molchanov Switzerland
Jaroslav Hájek Czechia
Piet Groeneboom relative to Tailen Hsing United States Tailen Hsing's profile →
Citations per field
00.5×1.5×
Tailen Hsing · 1×
Citations per year

Countries citing papers authored by Piet Groeneboom

Since Specialization
Citations

This map shows the geographic impact of Piet Groeneboom's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Piet Groeneboom with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Piet Groeneboom more than expected).

Fields of papers citing papers by Piet Groeneboom

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Piet Groeneboom. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Piet Groeneboom. The network helps show where Piet Groeneboom may publish in the future.

Co-authorship network of co-authors of Piet Groeneboom

This figure shows the co-authorship network connecting the top 25 collaborators of Piet Groeneboom. A scholar is included among the top collaborators of Piet Groeneboom based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Piet Groeneboom. Piet Groeneboom is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 18
3
Nonparametric Estimation under Shape Constraints
1
4 3
5 5
6 7
7 45
8 2
9 22
10 9
11 44
12 132
13
A canonical process for estimation of convex functions: the "invelope" of integrated Brownian motion + t4.
2
14 14
15 2
16 8
17 164
18 31
19 12
20 76

About Piet Groeneboom

Piet Groeneboom is a scholar working on Statistics and Probability, Finance and Applied Mathematics, having authored 63 papers that have together received 1.9k indexed citations. Recurring topics across this work include Statistical Methods and Inference (36 papers), Bayesian Methods and Mixture Models (19 papers) and Statistical Methods and Bayesian Inference (14 papers). The work is most often cited by research in Statistics and Probability (1.5k citations), Statistics, Probability and Uncertainty (187 citations) and Mathematical Physics (229 citations). Piet Groeneboom has collaborated with scholars based in Netherlands, United States and Belgium. Frequent co-authors include Jon A. Wellner, Geurt Jongbloed, J. Oosterhoff, Ronald B. Geskus, F.H. Ruymgaart, Hendrik P. Lopuhaä, Ronald Pyke, Eric Cator, Galen R. Shorack and Marloes H. Maathuis. Their work appears in journals such as Technometrics, The Annals of Statistics and Lecture notes in mathematics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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