J. Bert Keats

46 papers receiving 2.0k citations

Hit Papers

Statistical Methods for Reliability Data19992026200820171999100200300400

Peers

J. Bert Keats
Comparison fields: 5 of 120
  • Statistics, Probability and Uncertainty 1.3k
  • Statistics and Probability 814
  • Safety, Risk, Reliability and Quality 385
  • Management Science and Operations Research 339
  • Control and Systems Engineering 278
Replace T. N. Goh with:
T. N. Goh Singapore
Loon Ching Tang Singapore
Ming‐Hung Shu Taiwan
Fu‐Kwun Wang Taiwan
Tongdan Jin United States
Kenneth E. Case United States
Uday Kumar India
Kuei‐Hu Chang Taiwan
Edward Pohl United States
Daoud Aït‐Kadi Canada
J. Bert Keats relative to T. N. Goh Singapore T. N. Goh's profile →
Citations per field
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Citations per year

Countries citing papers authored by J. Bert Keats

Since Specialization
Citations

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

Fields of papers citing papers by J. Bert Keats

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J. Bert Keats. 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 J. Bert Keats. The network helps show where J. Bert Keats may publish in the future.

Co-authorship network of co-authors of J. Bert Keats

This figure shows the co-authorship network connecting the top 25 collaborators of J. Bert Keats. A scholar is included among the top collaborators of J. Bert Keats 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 J. Bert Keats. J. Bert Keats 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
Comparison of Parameter Estimation for Weibull Distribution
2
2 2
3 10
4 14
5 2
6 9
7 5
8 11
9 20
10 22
11 29
12 38
13 1
14 5
15 6
16 2
17 194
18 9
19 6
20 349

About J. Bert Keats

J. Bert Keats is a scholar working on Statistics, Probability and Uncertainty, Medical Laboratory Technology and Statistics and Probability, having authored 49 papers that have together received 2.2k indexed citations. Recurring topics across this work include Advanced Statistical Process Monitoring (27 papers), Scientific Measurement and Uncertainty Evaluation (15 papers) and Reliability and Maintenance Optimization (9 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (1.3k citations), Statistics and Probability (814 citations) and Medical Laboratory Technology (129 citations). J. Bert Keats has collaborated with scholars based in United States, Taiwan and Italy. Frequent co-authors include Douglas C. Montgomery, George C. Runger, Fu‐Kwun Wang, W. J. Zimmer, Sharad S. Prabhu, Eric R. Ziegel, Connie M. Borror, Enrique Del Castillo, Elart von Collani and Kenneth E. Case. Their work appears in journals such as Journal of the American Statistical Association, Technometrics and Operations Research.

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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