John P. Buonaccorsi
- Ecology top 2%
- Statistics and Probability top 0.5%
- Insect Science top 1%
- Nature and Landscape Conservation top 2%
- Ecology, Evolution, Behavior and Systematics top 2%
- Co-authors
- Joseph S. ElkintonGreg DwyerAndrew M. LiebholdJohn StaudenmayerDavid I. KingMark T. SmithH. R. SmithScott Evans
- Topics
- Advanced Statistical Methods and Models (20 papers)Statistical Methods and Bayesian Inference (17 papers)Optimal Experimental Design Methods (10 papers)
- Partner nations
- United StatesNorwayCanada
In The Last Decade
John P. Buonaccorsi
80 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 171
- Ecology 961
- Statistics and Probability 571
- Insect Science 522
- Nature and Landscape Conservation 489
- Ecology, Evolution, Behavior and Systematics 378
Countries citing papers authored by John P. Buonaccorsi
This map shows the geographic impact of John P. Buonaccorsi'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 John P. Buonaccorsi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John P. Buonaccorsi more than expected).
Fields of papers citing papers by John P. Buonaccorsi
This network shows the impact of papers produced by John P. Buonaccorsi. 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 John P. Buonaccorsi. The network helps show where John P. Buonaccorsi may publish in the future.
Co-authorship network of co-authors of John P. Buonaccorsi
This figure shows the co-authorship network connecting the top 25 collaborators of John P. Buonaccorsi. A scholar is included among the top collaborators of John P. Buonaccorsi 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 John P. Buonaccorsi. John P. Buonaccorsi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 5 | |
| 4 | 3 | |
| 5 | 10 | |
| 6 | 10 | |
| 7 | 6 | |
| 8 | 13 | |
| 9 | 59 | |
| 10 | 5 | |
| 11 | 5 | |
| 12 | 11 | |
| 13 | 10 | |
| 14 | 41 | |
| 15 | 41 | |
| 16 | 126 | |
| 17 | Estimation in longitudinal random effects models with measurement error | 25 |
| 18 | 187 | |
| 19 | 15 | |
| 20 | 11 |
About John P. Buonaccorsi
John P. Buonaccorsi is a scholar working on Statistics and Probability, Insect Science and Management Science and Operations Research, having authored 80 papers that have together received 2.9k indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (20 papers), Statistical Methods and Bayesian Inference (17 papers) and Optimal Experimental Design Methods (10 papers). The work is most often cited by research in Statistics and Probability (571 citations), Insect Science (522 citations) and Nature and Landscape Conservation (489 citations). John P. Buonaccorsi has collaborated with scholars based in United States, Norway and Canada. Frequent co-authors include Joseph S. Elkinton, Greg Dwyer, Andrew M. Liebhold, John Staudenmayer, David I. King, Mark T. Smith, H. R. Smith, Scott Evans, George H. Boettner and Richard M. DeGraaf. Their work appears in journals such as Journal of the American Statistical Association, The Astrophysical Journal and Ecology.
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.