John T. Webster

1.3k citations
35 papers · 972 · h-index 16

Impact in

Papers in

John T. Webster

32 papers receiving 854 citations

Peers

John T. Webster
Comparison fields: 5 of 150
  • Statistics and Probability 467
  • Statistics, Probability and Uncertainty 171
  • Analytical Chemistry 139
  • Management Science and Operations Research 118
  • Applied Mathematics 58
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Citations per field
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Citations per year

Countries citing papers authored by John T. Webster

Since Specialization
Citations

This map shows the geographic impact of John T. Webster'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 T. Webster with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John T. Webster more than expected).

Fields of papers citing papers by John T. Webster

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside John T. Webster, 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 T. Webster Line = papers co-authored together John T. Webster links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1974134
2 1975117
3 1972100
4 199077
5 198360
6 197656
7 197751
8 196548
9 196640
10
Fabricating construction components using layer manufacturing technology
200939
11 197436
12 197334
13 197527
14 198322
15 197320
16 199119
17 196514
18 197213
19 19919
20 19738

About John T. Webster

John T. Webster is a scholar working on Statistics and Probability, Management Science and Operations Research, Analytical Chemistry, Safety, Risk, Reliability and Quality and Applied Mathematics, having authored 35 papers that have together received 972 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (14 papers), Optimal Experimental Design Methods (8 papers), Spectroscopy and Chemometric Analyses (5 papers), Statistical Methods and Inference (4 papers), Statistical Distribution Estimation and Applications (3 papers), Multi-Criteria Decision Making (2 papers), Statistical Methods and Applications (2 papers) and Genetic and phenotypic traits in livestock (2 papers). The work is most often cited by research in Statistics and Probability (467 citations), Statistics, Probability and Uncertainty (171 citations), Analytical Chemistry (139 citations), Management Science and Operations Research (118 citations) and Applied Mathematics (58 citations). John T. Webster has collaborated with scholars based in United States and Ethiopia. Frequent co-authors include Richard F. Gunst, Robert L Mason, James M. Davenport, MARVIN N. LENTNER, Aman Ullah, Jon N. K. Rao, Hrishikesh D. Vinod, Edward R. Mansfield, Michael H. Ames and MICHAEL R. LEVY. Their work appears in journals such as Technometrics, The American Statistician, Journal of the American Statistical Association, Biometrika 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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