L. A. Baxter
Impact in
- Statistics and Probability top 5%
- Statistical Distribution Estimation and Applications
- Statistical Methods and Inference
- Advanced Statistical Methods and Models
- Statistical Methods and Bayesian Inference
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- Advanced Bandit Algorithms Research
Papers in
-
- Statistical Distribution Estimation and Applications 2
- Statistics Education and Methodologies 1
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- Reliability and Maintenance Optimization 3
- Co-authors
- Robert G. Bartle (1 shared paper)Michael Tortorella (1 shared paper)Qiqing Yu (1 shared paper)Stephen J. Finch (1 shared paper)
- Journals
- Journal of the Royal Statistical Society Series A (Statistics in Society) (2 papers)IEEE Transactions on Reliability (1 paper)Insurance Mathematics and Economics (1 paper)Statistics & Risk Modeling (1 paper)Journal of the Royal Statistical Society Series D (The Statistician) (1 paper)
- Partner nations
- United States
In The Last Decade
L. A. Baxter
8 papers receiving 225 citations
Peers
Comparison fields: 5 of 86
- Statistics and Probability 60
- Management Science and Operations Research 36
- Mathematical Physics 24
- Statistics, Probability and Uncertainty 18
- Applied Mathematics 22
Countries citing papers authored by L. A. Baxter
This map shows the geographic impact of L. A. Baxter'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 L. A. Baxter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites L. A. Baxter more than expected).
Fields of papers citing papers by L. A. Baxter
This network shows the impact of papers produced by L. A. Baxter. 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 L. A. Baxter. The network helps show where L. A. Baxter may publish in the future.
Co-authors
The 4 scholars most cited alongside L. A. Baxter, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 1996 | 131 | |
| 2 | 1991 | 64 | |
| 3 | 1990 | 39 | |
| 4 | 1989 | 4 | |
| 5 | 2002 | 3 | |
| 6 | 1995 | 2 | |
| 7 | 2002 | 1 | |
| 8 | 1998 | 1 |
About L. A. Baxter
L. A. Baxter is a scholar working on Statistics and Probability, Safety, Risk, Reliability and Quality, Management Science and Operations Research, Statistics, Probability and Uncertainty and Management Information Systems, having authored 8 papers that have together received 245 indexed citations. Recurring topics across this work include Reliability and Maintenance Optimization (3 papers), Probability and Risk Models (2 papers), Statistical Distribution Estimation and Applications (2 papers), Probabilistic and Robust Engineering Design (1 paper), Bayesian Methods and Mixture Models (1 paper), Advanced Queuing Theory Analysis (1 paper), Statistics Education and Methodologies (1 paper) and Air Quality and Health Impacts (1 paper). The work is most often cited by research in Statistics and Probability (60 citations), Management Science and Operations Research (36 citations), Mathematical Physics (24 citations), Statistics, Probability and Uncertainty (18 citations) and Applied Mathematics (22 citations). L. A. Baxter has collaborated with scholars based in United States. Frequent co-authors include Robert G. Bartle, Michael Tortorella, Qiqing Yu and Stephen J. Finch. Their work appears in journals such as Journal of the Royal Statistical Society Series A (Statistics in Society), IEEE Transactions on Reliability, Insurance Mathematics and Economics, Statistics & Risk Modeling and Journal of the Royal Statistical Society Series D (The Statistician).
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.