Anthony G. Pakes
- Mathematical Physics top 0.5%
- Stochastic processes and statistical mechanics 122
- Statistics and Probability top 0.2%
- Markov Chains and Monte Carlo Methods 44
- Statistical Distribution Estimation and Applications 25
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- Probability and Risk Models 54
- Finance top 1%
- Financial Risk and Volatility Modeling 21
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- Advanced Queuing Theory Analysis 24
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- Bayesian Methods and Mixture Models 56
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- Theoretical and Computational Physics 20
- Co-authors
- Yun LiF. W. SteutelEnkelejd HashorvaNorman KaplanValeri T. StefanovAdrian BaddeleyRobert GriffithsJesper Möller
- Journals
- SHILAP Revista de lepidopterología (3 papers)Journal of Ecology (1 paper)Operations Research (1 paper)
- Partner nations
- AustraliaUnited StatesChina
In The Last Decade
Anthony G. Pakes
175 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 93
- Mathematical Physics 1.4k
- Statistics and Probability 1.2k
- Management Science and Operations Research 969
- Finance 678
- Management Information Systems 476
Countries citing papers authored by Anthony G. Pakes
This map shows the geographic impact of Anthony G. Pakes'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 Anthony G. Pakes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anthony G. Pakes more than expected).
Fields of papers citing papers by Anthony G. Pakes
This network shows the impact of papers produced by Anthony G. Pakes. 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 Anthony G. Pakes. The network helps show where Anthony G. Pakes may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Anthony G. Pakes, 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 | 2024 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2017 | 1 | |
| 4 | 2013 | 6 | |
| 5 | 2011 | 15 | |
| 6 | 2010 | 3 | |
| 7 | 2010 | 26 | |
| 8 | Conditional Limit Theorems for Continuous Time and State Branching Process | 2008 | 0 |
| 9 | 2005 | 25 | |
| 10 | 2001 | 31 | |
| 11 | 1996 | 27 | |
| 12 | 1995 | 27 | |
| 13 | Characterizations by regressions of order statistics | 1995 | 4 |
| 14 | 1991 | 1 | |
| 15 | 1989 | 3 | |
| 16 | 1986 | 24 | |
| 17 | 1981 | 0 | |
| 18 | 1976 | 17 | |
| 19 | 1975 | 14 | |
| 20 | 1974 | 17 |
About Anthony G. Pakes
Anthony G. Pakes is a scholar working on Mathematical Physics, Statistics and Probability and Management Science and Operations Research, having authored 184 papers that have together received 2.8k indexed citations. Recurring topics across this work include Stochastic processes and statistical mechanics (122 papers), Bayesian Methods and Mixture Models (56 papers), Probability and Risk Models (54 papers), Markov Chains and Monte Carlo Methods (44 papers), Statistical Distribution Estimation and Applications (25 papers), Advanced Queuing Theory Analysis (24 papers), Financial Risk and Volatility Modeling (21 papers) and Theoretical and Computational Physics (20 papers). The work is most often cited by research in Mathematical Physics (1.4k citations), Statistics and Probability (1.2k citations) and Management Science and Operations Research (969 citations). Anthony G. Pakes has collaborated with scholars based in Australia, United States and China. Frequent co-authors include Yun Li, F. W. Steutel, Enkelejd Hashorva, Norman Kaplan, Valeri T. Stefanov, Adrian Baddeley, Robert Griffiths, Jesper Möller, Qihe Tang and Jorge Navarro. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Ecology 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.