Peter Neal
Impact in
- Modeling and Simulation top 0.5%
- COVID-19 epidemiological studies
- Statistics and Probability top 1%
- Statistical Methods and Bayesian Inference
- Markov Chains and Monte Carlo Methods
Papers in
-
- COVID-19 epidemiological studies 19
-
- Stochastic processes and statistical mechanics 24
- Co-authors
- Gareth O. RobertsFrank BallJérôme HamelinJonathan DushoffBart HaegemanJohn MoriartyJoshua S. WeitzTheodore Kypraios
- Journals
- Journal of Applied Probability (12 papers)Advances in Applied Probability (7 papers)Mathematical Biosciences (4 papers)Statistics and Computing (4 papers)Journal of Mathematical Biology (3 papers)
- Partner nations
- United KingdomSwedenCanada
In The Last Decade
Peter Neal
54 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 139
- Modeling and Simulation 416
- Statistics and Probability 267
- Statistical and Nonlinear Physics 209
- Mathematical Physics 114
- Agronomy and Crop Science 94
Countries citing papers authored by Peter Neal
This map shows the geographic impact of Peter Neal'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 Peter Neal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Neal more than expected).
Fields of papers citing papers by Peter Neal
This network shows the impact of papers produced by Peter Neal. 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 Peter Neal. The network helps show where Peter Neal may publish in the future.
Co-authorship network
The 21 scholars most cited alongside Peter Neal, 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 | 2025 | 0 | |
| 2 | 2023 | 2 | |
| 3 | 2023 | 1 | |
| 4 | 2017 | 15 | |
| 5 | 2016 | 9 | |
| 6 | 2014 | 2 | |
| 7 | 2012 | 7 | |
| 8 | 2009 | 14 | |
| 9 | 2008 | 11 | |
| 10 | 2008 | 9 | |
| 11 | 2008 | 96 | |
| 12 | 2007 | 11 | |
| 13 | Optimal Scaling of Random Walk Metropolis algorithms with\nDiscontinuous target densities | 2007 | 18 |
| 14 | 2006 | 30 | |
| 15 | 2005 | 1 | |
| 16 | 2005 | 2 | |
| 17 | 2004 | 52 | |
| 18 | 2003 | 4 | |
| 19 | 2003 | 18 | |
| 20 | 2002 | 138 |
About Peter Neal
Peter Neal is a scholar working on Modeling and Simulation, Mathematical Physics, Statistics and Probability, Statistical and Nonlinear Physics and Public Health, Environmental and Occupational Health, having authored 55 papers that have together received 1.3k indexed citations. Recurring topics across this work include Stochastic processes and statistical mechanics (24 papers), Mathematical and Theoretical Epidemiology and Ecology Models (23 papers), COVID-19 epidemiological studies (19 papers), Bayesian Methods and Mixture Models (19 papers), Complex Network Analysis Techniques (16 papers), Markov Chains and Monte Carlo Methods (13 papers), Statistical Methods and Bayesian Inference (10 papers) and Evolution and Genetic Dynamics (5 papers). The work is most often cited by research in Modeling and Simulation (416 citations), Statistics and Probability (267 citations), Statistical and Nonlinear Physics (209 citations), Mathematical Physics (114 citations) and Agronomy and Crop Science (94 citations). Peter Neal has collaborated with scholars based in United Kingdom, Sweden and Canada. Frequent co-authors include Gareth O. Roberts, Frank Ball, Frank Ball, Jérôme Hamelin, Jonathan Dushoff, Bart Haegeman, John Moriarty, Joshua S. Weitz, Theodore Kypraios and Chris Jewell. Their work appears in journals such as Journal of Applied Probability, Advances in Applied Probability, Mathematical Biosciences, Statistics and Computing and Journal of Mathematical Biology.
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.