Galin L. Jones
- Statistics and Probability top 0.2%
- Artificial Intelligence top 1%
- Statistics, Probability and Uncertainty top 1%
- Molecular Biology
- Economics and Econometrics top 5%
- Co-authors
- Andrew GelmanXiao‐Li MengSteve BrooksBrian CaffoJames P. HobertJames M. FlegalRonald C. NeathMurali Haran
- Topics
- Markov Chains and Monte Carlo Methods (26 papers)Statistical Methods and Inference (24 papers)Bayesian Methods and Mixture Models (19 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of the American Statistical AssociationJournal of Nutrition
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Galin L. Jones
56 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 195
- Statistics and Probability 1.1k
- Artificial Intelligence 933
- Statistics, Probability and Uncertainty 255
- Molecular Biology 198
- Economics and Econometrics 182
Countries citing papers authored by Galin L. Jones
This map shows the geographic impact of Galin L. Jones'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 Galin L. Jones with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Galin L. Jones more than expected).
Fields of papers citing papers by Galin L. Jones
This network shows the impact of papers produced by Galin L. Jones. 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 Galin L. Jones. The network helps show where Galin L. Jones may publish in the future.
Co-authorship network of co-authors of Galin L. Jones
This figure shows the co-authorship network connecting the top 25 collaborators of Galin L. Jones. A scholar is included among the top collaborators of Galin L. Jones 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 Galin L. Jones. Galin L. Jones is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 2 | |
| 3 | 10 | |
| 4 | 4 | |
| 5 | New visualizations for Monte Carlo simulations | 1 |
| 6 | 4 | |
| 7 | 21 | |
| 8 | 7 | |
| 9 | 24 | |
| 10 | Variable-at-a-time Implementations of Metropolis-Hastings | 3 |
| 11 | Component-wise Markov chain Monte Carlo | 4 |
| 12 | 26 | |
| 13 | Gibbs Sampling for a Bayesian Hierarchical Version of the General Linear Mixed Model | 6 |
| 14 | 8 | |
| 15 | Ascent-Based Monte Carlo EM | 18 |
| 16 | 82 | |
| 17 | 46 | |
| 18 | 19 | |
| 19 | 20 | |
| 20 | 17 |
About Galin L. Jones
Galin L. Jones is a scholar working on Statistics and Probability, Equine and Computational Mathematics, having authored 58 papers that have together received 3.3k indexed citations. Recurring topics across this work include Markov Chains and Monte Carlo Methods (26 papers), Statistical Methods and Inference (24 papers) and Bayesian Methods and Mixture Models (19 papers). The work is most often cited by research in Statistics and Probability (1.1k citations), Statistics, Probability and Uncertainty (255 citations) and Artificial Intelligence (933 citations). Galin L. Jones has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Andrew Gelman, Xiao‐Li Meng, Steve Brooks, Brian Caffo, James P. Hobert, James M. Flegal, Ronald C. Neath, Murali Haran, Richard C. Hill and Wolfgang Jank. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Journal of Nutrition.
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.