Steen A. Andersson

1.4k citations
26 papers · 836 indexed · h-index 16
Topics
Bayesian Modeling and Causal Inference (13 papers)Statistical Methods and Inference (5 papers)Bayesian Methods and Mixture Models (4 papers)

In The Last Decade

Steen A. Andersson

25 papers receiving 731 citations

Peers

Steen A. Andersson
Comparison fields: 5 of 91
  • Artificial Intelligence 605
  • Statistics and Probability 334
  • Computational Theory and Mathematics 145
  • Molecular Biology 116
  • Management Science and Operations Research 94
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Yasuko Chikuse Japan
Milan Studený Czechia
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Azaria Paz Israel
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Steen A. Andersson relative to Yasuko Chikuse Japan Yasuko Chikuse's profile →
Citations per field
00.5×10×16.6×
Yasuko Chikuse · 1×
Citations per year

Countries citing papers authored by Steen A. Andersson

Since Specialization
Citations

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

Fields of papers citing papers by Steen A. Andersson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Steen A. Andersson. 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 Steen A. Andersson. The network helps show where Steen A. Andersson may publish in the future.

Co-authorship network of co-authors of Steen A. Andersson

This figure shows the co-authorship network connecting the top 25 collaborators of Steen A. Andersson. A scholar is included among the top collaborators of Steen A. Andersson 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 Steen A. Andersson. Steen A. Andersson 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 2
2 12
3 4
4 15
5 7
6 90
7 19
8 2
9 14
10 50
11 243
12 78
13 18
14 1
15 9
16
The lattice structure of orthogonal linear models and orthogonal variance component models
12
17 17
18 47
19 34
20 53

About Steen A. Andersson

Steen A. Andersson is a scholar working on Statistics and Probability, Artificial Intelligence and Computational Theory and Mathematics, having authored 26 papers that have together received 836 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (13 papers), Statistical Methods and Inference (5 papers) and Bayesian Methods and Mixture Models (4 papers). The work is most often cited by research in Statistics and Probability (334 citations), Artificial Intelligence (605 citations) and Computational Theory and Mathematics (145 citations). Steen A. Andersson has collaborated with scholars based in United States, Denmark and Germany. Frequent co-authors include Michael D. Perlman, David Madigan, Chris Volinsky, Søren Jensen, Jesper Madsen, Christopher M. Triggs, Thomas Klein and Mathias Drton. Their work appears in journals such as Statistics in Medicine, The Annals of Statistics and Linear Algebra and its Applications.

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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