Stuart Barber

966 citations
33 papers · 716 · h-index 13

Impact in

    • Statistical Methods in Clinical Trials
    • Markov Chains and Monte Carlo Methods
    • Statistical Methods and Inference
    • Phytochemicals and Antioxidant Activities

Papers in

Stuart Barber

32 papers receiving 687 citations

Peers

Stuart Barber
Comparison fields: 5 of 149
  • Statistics and Probability 166
  • Biochemistry 21
  • Neurology 30
  • Statistics, Probability and Uncertainty 18
  • Artificial Intelligence 72
Replace Johan Lim with:
Johan Lim South Korea
Yiwei Zhang China
Eric F. Lock United States
 An China
Nouna Kettaneh Sweden
Isobel Claire Gormley Ireland
Michail Tsagris Greece
Xin Gao Canada
Arthur Tenenhaus France
Ravindra Khattree United States
Stuart Barber relative to Johan Lim South Korea Johan Lim's profile →
Citations per field
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Citations per year

Countries citing papers authored by Stuart Barber

Since Specialization
Citations

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

Fields of papers citing papers by Stuart Barber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004223
2 200983
3 201551
4 200248
5 200440
6 201139
7 201537
8 201825
9 200222
10 201918
11 201317
12 199914
13 201813
14 201911
15 20229
16 20138
17 20188
18 20226
19 20135
20 20155

About Stuart Barber

Stuart Barber is a scholar working on Statistics and Probability, Signal Processing, Transportation, Artificial Intelligence and Applied Mathematics, having authored 33 papers that have together received 716 indexed citations. Recurring topics across this work include Statistical Methods in Epidemiology (5 papers), Time Series Analysis and Forecasting (4 papers), Genomics and Phylogenetic Studies (4 papers), Statistical Methods and Inference (3 papers), Evolution and Genetic Dynamics (2 papers), Image and Signal Denoising Methods (2 papers), Spatial and Panel Data Analysis (2 papers) and Point processes and geometric inequalities (2 papers). The work is most often cited by research in Statistics and Probability (166 citations), Biochemistry (21 citations), Neurology (30 citations), Statistics, Probability and Uncertainty (18 citations) and Artificial Intelligence (72 citations). Stuart Barber has collaborated with scholars based in United Kingdom, United States and China. Frequent co-authors include Guy P. Nason, Graham Richard Law, Paul David Baxter, Claire M Keeble, Pamela J. Shaw, Adrian Higginbottom, Siân C. Barber, Richard J. Mead, Jochen Voß and Gary Williamson. Their work appears in journals such as Biometrics, Journal of the Royal Statistical Society Series B (Statistical Methodology), Journal of the Royal Statistical Society Series C (Applied Statistics), Computational Statistics & Data Analysis and Journal of Transport & Health.

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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