Fred Huffer
Impact in
- Pollution top 5%
- Oil Spill Detection and Mitigation
- Statistics and Probability top 5%
Papers in
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- Bayesian Methods and Mixture Models 5
-
- Statistical Distribution Estimation and Applications 3
- Statistical Methods and Inference 3
- Co-authors
- Hulin Wu (1 shared paper)Andrew Beet (1 shared paper)Ian R. MacDonald (1 shared paper)Deborah French-McCay (1 shared paper)Samira Daneshgar Asl (1 shared paper)Lian Feng (1 shared paper)George Graettinger (1 shared paper)Andrew R. Solow (1 shared paper)
- Journals
- Journal of Applied Probability (4 papers)Journal of Geophysical Research Oceans (1 paper)Environmental and Ecological Statistics (1 paper)PLoS Computational Biology (1 paper)Geographical Analysis (1 paper)
- Partner nations
- United States
In The Last Decade
Fred Huffer
16 papers receiving 404 citations
Peers
Comparison fields: 5 of 88
- Pollution 157
- Statistics and Probability 61
- Oceanography 87
- Ecological Modeling 29
- Global and Planetary Change 117
Countries citing papers authored by Fred Huffer
This map shows the geographic impact of Fred Huffer'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 Fred Huffer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fred Huffer more than expected).
Fields of papers citing papers by Fred Huffer
This network shows the impact of papers produced by Fred Huffer. 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 Fred Huffer. The network helps show where Fred Huffer may publish in the future.
Co-authors
The 23 scholars most cited alongside Fred Huffer, 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 | 2015 | 202 | |
| 2 | 1997 | 104 | |
| 3 | 2019 | 35 | |
| 4 | 1988 | 23 | |
| 5 | 1988 | 15 | |
| 6 | 2008 | 13 | |
| 7 | 2016 | 11 | |
| 8 | 2019 | 5 | |
| 9 | 2020 | 4 | |
| 10 | 1986 | 3 | |
| 11 | 2017 | 3 | |
| 12 | 1986 | 2 | |
| 13 | 2014 | 2 | |
| 14 | 2010 | 1 | |
| 15 | 2016 | 1 | |
| 16 | 2010 | 1 |
About Fred Huffer
Fred Huffer is a scholar working on Artificial Intelligence, Statistics and Probability, Economics and Econometrics, Molecular Biology and Numerical Analysis, having authored 16 papers that have together received 425 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (5 papers), Statistical Distribution Estimation and Applications (3 papers), Statistical Methods and Inference (3 papers), Spatial and Panel Data Analysis (3 papers), Point processes and geometric inequalities (2 papers), Mathematical Approximation and Integration (2 papers), Gene expression and cancer classification (2 papers) and Probability and Risk Models (2 papers). The work is most often cited by research in Pollution (157 citations), Statistics and Probability (61 citations), Oceanography (87 citations), Ecological Modeling (29 citations) and Global and Planetary Change (117 citations). Fred Huffer has collaborated with scholars based in United States. Frequent co-authors include Hulin Wu, Andrew Beet, Ian R. MacDonald, Deborah French-McCay, Samira Daneshgar Asl, Lian Feng, George Graettinger, Andrew R. Solow, Gregg A. Swayze and Oscar Garcia‐Pineda. Their work appears in journals such as Journal of Applied Probability, Journal of Geophysical Research Oceans, Environmental and Ecological Statistics, PLoS Computational Biology and Geographical Analysis.
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.