Peter McCullagh
- Statistics and Probability top 0.01%
- Statistical Methods and Bayesian Inference 21
- Statistical Methods and Inference 20
- Advanced Statistical Methods and Models 17
- Statistical Distribution Estimation and Applications 16
- Ecological Modeling top 0.5%
- Nature and Landscape Conservation top 0.5%
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- Immune Response and Inflammation 20
- T-cell and B-cell Immunology 18
- Reproductive System and Pregnancy 10
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- Bayesian Methods and Mixture Models 16
- Co-authors
- J. A. NelderTerry M. TherneauIb M. SkovgaardGauss M. CordeiroGary GlonekZhenming ShunRobert TibshiraniRobert J. Baker
- Journals
- Immunology and Cell Biology (18 papers)Biometrika (17 papers)Journal of the Royal Statistical Society Series B (Statistical Methodology) (10 papers)
- Partner nations
- AustraliaUnited StatesUnited Kingdom
In The Last Decade
Peter McCullagh
150 papers receiving 23.7k citations
Hit Papers
Peers
Comparison fields: 5 of 236
- Statistics and Probability 7.0k
- Ecological Modeling 1.1k
- Nature and Landscape Conservation 2.6k
- Management Science and Operations Research 1.8k
- Statistics, Probability and Uncertainty 923
Countries citing papers authored by Peter McCullagh
This map shows the geographic impact of Peter McCullagh'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 McCullagh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter McCullagh more than expected).
Fields of papers citing papers by Peter McCullagh
This network shows the impact of papers produced by Peter McCullagh. 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 McCullagh. The network helps show where Peter McCullagh may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Peter McCullagh, 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 | 2023 | 3 | |
| 2 | 2023 | 1 | |
| 3 | 2023 | 4 | |
| 4 | 2018 | 5 | |
| 5 | The pilgrim's process | 2014 | 0 |
| 6 | 2013 | 0 | |
| 7 | 2012 | 3 | |
| 8 | Classification Based on Permanental Process with Cyclic Approximations | 2011 | 1 |
| 9 | 2003 | 1 | |
| 10 | 2003 | 37 | |
| 11 | 2003 | 3 | |
| 12 | 2002 | 2 | |
| 13 | 2001 | 4 | |
| 14 | 2001 | 2 | |
| 15 | 2000 | 2 | |
| 16 | 1998 | 2 | |
| 17 | 1993 | 8 | |
| 18 | 1992 | 2 | |
| 19 | 1989 | 25 | |
| 20 | 1989 | 26 |
About Peter McCullagh
Peter McCullagh is a scholar working on Statistics and Probability, Immunology and Applied Mathematics, having authored 156 papers that have together received 25.3k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (21 papers), Statistical Methods and Inference (20 papers), Immune Response and Inflammation (20 papers), T-cell and B-cell Immunology (18 papers), Advanced Statistical Methods and Models (17 papers), Bayesian Methods and Mixture Models (16 papers), Statistical Distribution Estimation and Applications (16 papers) and Reproductive System and Pregnancy (10 papers). The work is most often cited by research in Statistics and Probability (7.0k citations), Ecological Modeling (1.1k citations) and Nature and Landscape Conservation (2.6k citations). Peter McCullagh has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include J. A. Nelder, Terry M. Therneau, Ib M. Skovgaard, Gauss M. Cordeiro, Gary Glonek, Zhenming Shun, Robert Tibshirani, Robert J. Baker, Alan Agresti and David A. Williams. Their work appears in journals such as Immunology and Cell Biology, Biometrika, Journal of the Royal Statistical Society Series B (Statistical Methodology), Journal of the American Statistical Association and The Annals of Statistics.
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.