Geoffrey S. Watson

9.9k citations
50 papers · 7.7k indexed · 2 hit papers · h-index 21
Topics
Bayesian Methods and Mixture Models (10 papers)Geomagnetism and Paleomagnetism Studies (8 papers)Soil Geostatistics and Mapping (6 papers)

In The Last Decade

Geoffrey S. Watson

44 papers receiving 7.0k citations

Hit Papers

Circular Statistics in Biology19642026198420051982196410002.0k3.0k4.0k

Peers

Geoffrey S. Watson
Comparison fields: 5 of 206
  • Ecology 1.4k
  • Statistics and Probability 1.2k
  • Ecology, Evolution, Behavior and Systematics 1.0k
  • Cognitive Neuroscience 912
  • Artificial Intelligence 829
Replace N. I. Fisher with:
N. I. Fisher Australia
David R. Brillinger United States
Stephen Roberts United Kingdom
Kanti V. Mardia United Kingdom
Kenneth Lange United States
Edward Batschelet Switzerland
Pietro Perona United States
Adrian Baddeley Australia
José C. Pinheiro Brazil
Peter Sprent United Kingdom
Geoffrey S. Watson relative to N. I. Fisher Australia N. I. Fisher's profile →
Citations per field
00.5×2.7×
N. I. Fisher · 1×
Citations per year

Countries citing papers authored by Geoffrey S. Watson

Since Specialization
Citations

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

Fields of papers citing papers by Geoffrey S. Watson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Geoffrey S. Watson. 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 Geoffrey S. Watson. The network helps show where Geoffrey S. Watson may publish in the future.

Co-authorship network of co-authors of Geoffrey S. Watson

This figure shows the co-authorship network connecting the top 25 collaborators of Geoffrey S. Watson. A scholar is included among the top collaborators of Geoffrey S. Watson 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 Geoffrey S. Watson. Geoffrey S. Watson 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 1
2 2
3 1
4 16
5 19
6 1
7 1
8 4
9 0
10 8
11 5
12 19
13 21
14 35
15 37
16 125
17 18
18 2
19 105
20
Serial correlation in regression analysis, Biometrika, 1955-1956, 4.2 & 4.3
2

About Geoffrey S. Watson

Geoffrey S. Watson is a scholar working on Statistics and Probability, Applied Mathematics and Mathematical Physics, having authored 50 papers that have together received 7.7k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (10 papers), Geomagnetism and Paleomagnetism Studies (8 papers) and Soil Geostatistics and Mapping (6 papers). The work is most often cited by research in Statistics and Probability (1.2k citations), Developmental Biology (203 citations) and Ecology (1.4k citations). Geoffrey S. Watson has collaborated with scholars based in United States, Australia and Canada. Frequent co-authors include Edward Batschelet, Randolph J. Enkin, Michel David, Ernst Caspari, Peter Bloomfield, Philip Hartman, Massimo Guarascio, D. Blöch, T. C. Onstott and John T. Kent. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.

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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