John Bibby

2.1k citations
30 papers · 1.5k · h-index 14

Impact in

Papers in

John Bibby

25 papers receiving 1.5k citations

Peers

John Bibby
Comparison fields: 5 of 175
  • Agronomy and Crop Science 468
  • Animal Science and Zoology 272
  • Statistics and Probability 218
  • Genetics 341
  • Process Chemistry and Technology 33
Replace J. H. Matis with:
J. H. Matis United States
F. J. RICHARDS United Kingdom
A. P. Verbyla Australia
Kenneth J. Koehler United States
G. Tunnicliffe Wilson United Kingdom
Walter T. Fédérer United States
Magne Aldrin Norway
H. D. Patterson United Kingdom
Clarice Garcia Borges Demétrio Brazil
C. D. Kemp United Kingdom
John Bibby relative to J. H. Matis United States J. H. Matis's profile →
Citations per field
00.5×10×16.5×
J. H. Matis · 1×
Citations per year

Countries citing papers authored by John Bibby

Since Specialization
Citations

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

Fields of papers citing papers by John Bibby

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 19 scholars most cited alongside John Bibby, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with John Bibby Line = papers co-authored together John Bibby links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1979355
2 1978299
3 1981169
4 1979166
5 1981115
6 1974103
7 197986
8 198868
9 197740
10 197230
11 197529
12 197315
13 196715
14 197815
15 198711
16 19898
17 19777
18 19803
19 19942
20 19832

About John Bibby

John Bibby is a scholar working on Statistics and Probability, Sociology and Political Science, Statistical and Nonlinear Physics, Computational Theory and Mathematics and Political Science and International Relations, having authored 30 papers that have together received 1.5k indexed citations. Recurring topics across this work include Statistics Education and Methodologies (5 papers), Advanced Statistical Methods and Models (2 papers), Advanced Statistical Process Monitoring (1 paper), Advanced Mathematical Theories and Applications (1 paper), Neural Networks and Applications (1 paper), Matrix Theory and Algorithms (1 paper), Urban Transport and Accessibility (1 paper) and Optimization and Variational Analysis (1 paper). The work is most often cited by research in Agronomy and Crop Science (468 citations), Animal Science and Zoology (272 citations), Statistics and Probability (218 citations), Genetics (341 citations) and Process Chemistry and Technology (33 citations). John Bibby has collaborated with scholars based in United Kingdom, United States and India. Frequent co-authors include Helge Toutenburg, W. D. Ray, C. D. Sinclair, Y. L. Tong, J. Douglas Carroll, J. T. Kent, Tony Greenfield, K. V. Mardia, Lincoln E. Moses and Thomas J. Boardman. Their work appears in journals such as Biometrics, Quality & Quantity, Journal of the American Statistical Association, Journal of the Operational Research Society and Journal of the Royal Statistical Society Series C (Applied 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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