Dan Grove
Impact in
- Statistics and Probability top 5%
- Statistical Methods and Inference
- Advanced Statistical Methods and Models
-
- Ecology and Vegetation Dynamics Studies
- Fish Ecology and Management Studies
Papers in
- Co-authors
- G. Kitagawa (1 shared paper)Yoshitaka Sakamoto (1 shared paper)Makio Ishiguro (1 shared paper)Vic Barnett (1 shared paper)Linda Torczon (2 shared papers)Carole Roberts (1 shared paper)Marc S. Schneider (2 shared papers)R. D. Marangoni (2 shared papers)
- Journals
- Plastic & Reconstructive Surgery (2 papers)Technometrics (2 papers)Movement Ecology (1 paper)Parasitology (1 paper)ACM SIGPLAN Notices (1 paper)
- Partner nations
- United KingdomUnited StatesSpain
In The Last Decade
Dan Grove
12 papers receiving 1.1k citations
Dan Grove's Hit Papers
Peers
Comparison fields: 5 of 178
- Statistics and Probability 139
- Nature and Landscape Conservation 145
- Ecological Modeling 44
- Software 39
- Ecology 176
Countries citing papers authored by Dan Grove
This map shows the geographic impact of Dan Grove'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 Dan Grove with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Grove more than expected).
Fields of papers citing papers by Dan Grove
This network shows the impact of papers produced by Dan Grove. 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 Dan Grove. The network helps show where Dan Grove may publish in the future.
Co-authors
The 12 scholars most cited alongside Dan Grove, 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 | Akaike Information Criterion Statistics. Hit paper breakdown → | 1988 | 1034 |
| 2 | 1974 | 67 | |
| 3 | 1993 | 51 | |
| 4 | 1988 | 17 | |
| 5 | 1991 | 15 | |
| 6 | 1993 | 11 | |
| 7 | 1980 | 11 | |
| 8 | 1980 | 9 | |
| 9 | 1988 | 3 | |
| 10 | 2024 | 1 | |
| 11 | 1984 | 1 | |
| 12 | 1991 | 1 | |
| 13 | 2025 | 0 |
About Dan Grove
Dan Grove is a scholar working on Surgery, Oncology, Computational Theory and Mathematics, Management Science and Operations Research and Genetics, having authored 13 papers that have together received 1.2k indexed citations. Recurring topics across this work include Cutaneous Melanoma Detection and Management (2 papers), Software Reliability and Analysis Research (2 papers), Body Contouring and Surgery (2 papers), Software Testing and Debugging Techniques (2 papers), Formal Methods in Verification (2 papers), Optimal Experimental Design Methods (2 papers), Forensic and Genetic Research (1 paper) and Urbanization and City Planning (1 paper). The work is most often cited by research in Statistics and Probability (139 citations), Nature and Landscape Conservation (145 citations), Ecological Modeling (44 citations), Software (39 citations) and Ecology (176 citations). Dan Grove has collaborated with scholars based in United Kingdom, United States and Spain. Frequent co-authors include G. Kitagawa, Yoshitaka Sakamoto, Makio Ishiguro, Vic Barnett, Linda Torczon, Carole Roberts, Marc S. Schneider, R. D. Marangoni, Rebecca Butler and M. Wilber. Their work appears in journals such as Plastic & Reconstructive Surgery, Technometrics, Movement Ecology, Parasitology and ACM SIGPLAN Notices.
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.