Glen Meeden
- Statistics and Probability top 0.5%
- Artificial Intelligence top 5%
- Economics and Econometrics top 10%
- Statistics, Probability and Uncertainty top 2%
- Finance top 5%
- Co-authors
- Richard A. GroeneveldMalay GhoshStephen B. VardemanSueli Aparecida MingotiKun HeBarry C. ArnoldSiamak NoorbaloochiHenry E. Kyburg
- Topics
- Bayesian Methods and Mixture Models (34 papers)Statistical Methods and Bayesian Inference (24 papers)Survey Sampling and Estimation Techniques (21 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of the American Statistical AssociationTechnometrics
- Partner nations
- United StatesSouth KoreaIreland
In The Last Decade
Glen Meeden
84 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 165
- Statistics and Probability 568
- Artificial Intelligence 303
- Economics and Econometrics 137
- Statistics, Probability and Uncertainty 117
- Finance 114
Countries citing papers authored by Glen Meeden
This map shows the geographic impact of Glen Meeden'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 Glen Meeden with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Glen Meeden more than expected).
Fields of papers citing papers by Glen Meeden
This network shows the impact of papers produced by Glen Meeden. 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 Glen Meeden. The network helps show where Glen Meeden may publish in the future.
Co-authorship network of co-authors of Glen Meeden
This figure shows the co-authorship network connecting the top 25 collaborators of Glen Meeden. A scholar is included among the top collaborators of Glen Meeden 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 Glen Meeden. Glen Meeden is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | An Improved Skewness Measure | 5 |
| 2 | 2 | |
| 3 | 5 | |
| 4 | Exploring Imprecise Probability Assessments Based on Linear Constraints. | 3 |
| 5 | 2 | |
| 6 | 0 | |
| 7 | MEDIAN ESTIMATION USING AUXILIARY INFORMATION | 16 |
| 8 | 3 | |
| 9 | 5 | |
| 10 | 25 | |
| 11 | 20 | |
| 12 | 1 | |
| 13 | 1 | |
| 14 | 11 | |
| 15 | Admissibility of the MLE of the normal integer mean | 9 |
| 16 | 6 | |
| 17 | 14 | |
| 18 | 59 | |
| 19 | 1 | |
| 20 | 2 |
About Glen Meeden
Glen Meeden is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Artificial Intelligence, having authored 95 papers that have together received 1.2k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (34 papers), Statistical Methods and Bayesian Inference (24 papers) and Survey Sampling and Estimation Techniques (21 papers). The work is most often cited by research in Statistics and Probability (568 citations), Statistics, Probability and Uncertainty (117 citations) and Finance (114 citations). Glen Meeden has collaborated with scholars based in United States, South Korea and Ireland. Frequent co-authors include Richard A. Groeneveld, Malay Ghosh, Stephen B. Vardeman, Sueli Aparecida Mingoti, Kun He, Barry C. Arnold, Malay Ghosh, Siamak Noorbaloochi, Henry E. Kyburg and David Nelson. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Technometrics.
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.