R. A. Bailey

131 papers receiving 2.1k citations

Peers

R. A. Bailey
Comparison fields: 5 of 170
  • Discrete Mathematics and Combinatorics 268
  • Management Science and Operations Research 795
  • Statistics and Probability 393
  • Computational Theory and Mathematics 664
  • Geometry and Topology 140
Replace Michael D. Perlman with:
Michael D. Perlman United States
Walter T. Fédérer United States
Götz Trenkler Germany
Colin L. Mallows United States
D. A. Sprott Canada
Alan Tucker United States
Sasanka Roy India
Yasunori Fujikoshi Japan
H. V. Henderson New Zealand
Madan L. Puri United States
R. A. Bailey relative to Michael D. Perlman United States Michael D. Perlman's profile →
Citations per field
00.5×9.9×
Michael D. Perlman · 1×
Citations per year

Countries citing papers authored by R. A. Bailey

Since Specialization
Citations

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

Fields of papers citing papers by R. A. Bailey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside R. A. Bailey, 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 R. A. Bailey Line = papers co-authored together R. A. Bailey links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 136 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008172
2 1997162
3 2011152
4 199789
5 199382
6 201476
7 198469
8 198162
9 200857
10 200452
11 198347
12 197746
13 201142
14 200642
15 199640
16 200438
17 200538
18 199137
19 199136
20 198234

About R. A. Bailey

R. A. Bailey is a scholar working on Management Science and Operations Research, Electrical and Electronic Engineering, Computational Theory and Mathematics, Artificial Intelligence and Statistics and Probability, having authored 136 papers that have together received 2.3k indexed citations. Recurring topics across this work include Optimal Experimental Design Methods (63 papers), graph theory and CDMA systems (58 papers), Coding theory and cryptography (21 papers), Statistical Methods in Clinical Trials (18 papers), Finite Group Theory Research (14 papers), Advanced Multi-Objective Optimization Algorithms (11 papers), Graph Labeling and Dimension Problems (9 papers) and DNA and Biological Computing (7 papers). The work is most often cited by research in Discrete Mathematics and Combinatorics (268 citations), Management Science and Operations Research (795 citations), Statistics and Probability (393 citations), Computational Theory and Mathematics (664 citations) and Geometry and Topology (140 citations). R. A. Bailey has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Peter J‎. Cameron, Jean‐Marc Azäis, H. D. Patterson, Chris Brien, Terence P. Speed, M. F. Franklin, Julia Reiss, Karen Meagher, Hervé Monod and S. P. Burns. Their work appears in journals such as Biometrika, Discrete Mathematics, Journal of Statistical Planning and Inference, Journal of the Royal Statistical Society Series B (Statistical Methodology) 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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