Thomas Sellke

27 papers receiving 2.0k citations

Hit Papers

Testing a Point Null Hypothesis: The Irreconcilability of...198720262000201319872001100200300400500

Peers

Thomas Sellke
Comparison fields: 5 of 167
  • Statistics and Probability 961
  • Statistics, Probability and Uncertainty 424
  • Artificial Intelligence 400
  • Management Science and Operations Research 291
  • Economics and Econometrics 279
Replace David Cox with:
David Cox United Kingdom
V. P. Godambe Canada
Lucien LeCam
C. R. Rao United States
Richard L. Dykstra United States
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Craig Robertson United States
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Malay Ghosh United States
Thomas Sellke relative to David Cox United Kingdom David Cox's profile →
Citations per field
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David Cox · 1×
Citations per year

Countries citing papers authored by Thomas Sellke

Since Specialization
Citations

This map shows the geographic impact of Thomas Sellke'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 Thomas Sellke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Sellke more than expected).

Fields of papers citing papers by Thomas Sellke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas Sellke. 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 Thomas Sellke. The network helps show where Thomas Sellke may publish in the future.

Co-authorship network of co-authors of Thomas Sellke

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Sellke. A scholar is included among the top collaborators of Thomas Sellke 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 Thomas Sellke. Thomas Sellke 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 68
2 3
3 8
4 1
5 1
6 1
7 7
8 1
9 13
10
Stack Filters and Free Distributive Lattices
10
11 5
12 351
13 11
14 2
15 3
16 163
17 106
18 119
19 34
20
Large Sample Theory for Sequential Analysis of the Proportional Hazards Model.
1

About Thomas Sellke

Thomas Sellke is a scholar working on Statistics and Probability, Mathematical Physics and General Decision Sciences, having authored 27 papers that have together received 2.1k indexed citations. Recurring topics across this work include Stochastic processes and statistical mechanics (5 papers), Statistical Methods and Bayesian Inference (4 papers) and Statistical Methods and Inference (4 papers). The work is most often cited by research in Statistics and Probability (961 citations), Statistics, Probability and Uncertainty (424 citations) and Management Science and Operations Research (291 citations). Thomas Sellke has collaborated with scholars based in United States, Canada and Spain. Frequent co-authors include James O. Berger, M. J. Bayarri, J. Michael Harrison, Allison J. Taylor, David Siegmund, Edward J. Coyle, J.-H. Lin, Daniel J. Benjamin, Hani Doss and Steven P. Lalley. Their work appears in journals such as Journal of the American Statistical Association, Biometrika and The Annals of Statistics.

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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