Benjamin A. Shaby

1.5k total citations
30 papers, 881 citations indexed

About

Benjamin A. Shaby is a scholar working on Environmental Engineering, Global and Planetary Change and Economics and Econometrics. According to data from OpenAlex, Benjamin A. Shaby has authored 30 papers receiving a total of 881 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Environmental Engineering, 12 papers in Global and Planetary Change and 9 papers in Economics and Econometrics. Recurrent topics in Benjamin A. Shaby's work include Soil Geostatistics and Mapping (10 papers), Hydrology and Drought Analysis (8 papers) and Spatial and Panel Data Analysis (7 papers). Benjamin A. Shaby is often cited by papers focused on Soil Geostatistics and Mapping (10 papers), Hydrology and Drought Analysis (8 papers) and Spatial and Panel Data Analysis (7 papers). Benjamin A. Shaby collaborates with scholars based in United States, Spain and Saudi Arabia. Benjamin A. Shaby's co-authors include Brian J. Reich, Steven Finkbeiner, Montserrat Arrasate, Cari G. Kaufman, D. Michael Ando, Eliezer Masliah, David Ruppert, Jason Miller, Siddhartha Mitra and Sami J. Barmada and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and Journal of the American Statistical Association.

In The Last Decade

Benjamin A. Shaby

30 papers receiving 860 citations

Peers

Benjamin A. Shaby

GPC

CMN

Ganna Leonenko United Kingdom

Manuel G. Scotto Portugal

Zixing Fang United States

Mark S. Kaiser United States

N. C. Weber Australia

Alberto de la Fuente Chile

Julie Zhou Canada

Agostino Di Ciaccio Italy

James Xu Australia

Rosa M. Crujeiras Spain

Ganna Leonenko United Kingdom

Benjamin A. Shaby

242 ×0.9

106 ×0.5

GPC

152 ×0.8

22 ×0.1

CMN

21 ×0.2

Citations per year, relative to Benjamin A. Shaby Benjamin A. Shaby (= 1×) peers Ganna Leonenko

Countries citing papers authored by Benjamin A. Shaby

Since Specialization

Citations

This map shows the geographic impact of Benjamin A. Shaby'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 Benjamin A. Shaby with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin A. Shaby more than expected).

Fields of papers citing papers by Benjamin A. Shaby

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Benjamin A. Shaby. 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 Benjamin A. Shaby. The network helps show where Benjamin A. Shaby may publish in the future.

Co-authorship network of co-authors of Benjamin A. Shaby

This figure shows the co-authorship network connecting the top 25 collaborators of Benjamin A. Shaby. A scholar is included among the top collaborators of Benjamin A. Shaby 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 Benjamin A. Shaby. Benjamin A. Shaby is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Shaby, Benjamin A., et al.. (2025). Semiparametric Estimation of the Shape of the Limiting Bivariate Point Cloud. Bayesian Analysis. -1(-1). 3 indexed citations

Hanks, Ephraim M., et al.. (2024). Modeling First Arrival of Migratory Birds Using a Hierarchical Max-Infinitely Divisible Process. Journal of Agricultural Biological and Environmental Statistics. 30(4). 903–918. 1 indexed citations

Shaby, Benjamin A., et al.. (2024). Anthropogenic and meteorological effects on the counts and sizes of moderate and extreme wildfires. Environmetrics. 35(7). 1 indexed citations

Reich, Brian J., et al.. (2024). Modeling extremal streamflow using deep learning approximations and a flexible spatial process. The Annals of Applied Statistics. 18(2). 6 indexed citations

Shaby, Benjamin A., et al.. (2021). A Vecchia approximation for high-dimensional Gaussian cumulative distribution functions arising from spatial data. Journal of Statistical Computation and Simulation. 92(9). 1977–1994. 3 indexed citations

Shaby, Benjamin A., et al.. (2021). Hierarchical Transformed Scale Mixtures for Flexible Modeling of Spatial Extremes on Datasets With Many Locations. Figshare. 14 indexed citations

Shaby, Benjamin A., et al.. (2020). Machine learning for modeling animal movement. PLoS ONE. 15(7). e0235750–e0235750. 41 indexed citations

Shaby, Benjamin A., et al.. (2020). A Hierarchical Max-Infinitely Divisible Spatial Model for Extreme Precipitation. Journal of the American Statistical Association. 116(533). 93–106. 16 indexed citations

Reich, Brian J., et al.. (2018). A semiparametric Bayesian model for spatiotemporal extremes. arXiv (Cornell University). 2 indexed citations

10.

Reich, Brian J. & Benjamin A. Shaby. (2018). A Spatial Markov Model for Climate Extremes. Journal of Computational and Graphical Statistics. 28(1). 117–126. 14 indexed citations

11.

Hanks, Ephraim M., et al.. (2018). Extreme Value-Based Methods for Modeling Elk Yearly Movements. Journal of Agricultural Biological and Environmental Statistics. 24(1). 73–91. 6 indexed citations

12.

Skibinski, Gaia, D. Michael Ando, Aaron Daub, et al.. (2016). Nrf2 mitigates LRRK2- and α-synuclein–induced neurodegeneration by modulating proteostasis. Proceedings of the National Academy of Sciences. 114(5). 1165–1170. 99 indexed citations

13.

Stephenson, Alec, Benjamin A. Shaby, Brian J. Reich, & Andrew Sullivan. (2014). Estimating Spatially Varying Severity Thresholds of a Forest Fire Danger Rating System Using Max-Stable Extreme-Event Modeling. Journal of Applied Meteorology and Climatology. 54(2). 395–407. 14 indexed citations

14.

Tsvetkov, Andrey S., Montserrat Arrasate, Sami J. Barmada, et al.. (2013). Proteostasis of polyglutamine varies among neurons and predicts neurodegeneration. Nature Chemical Biology. 9(9). 586–592. 136 indexed citations

15.

Eidsvik, Jo, Benjamin A. Shaby, Brian J. Reich, Matthew W. Wheeler, & Jarad Niemi. (2013). Estimation and Prediction in Spatial Models With Block Composite Likelihoods. Journal of Computational and Graphical Statistics. 23(2). 295–315. 84 indexed citations

16.

Reich, Brian J. & Benjamin A. Shaby. (2012). A hierarchical max-stable spatial model for extreme precipitation. The Annals of Applied Statistics. 6(4). 1430–1451. 103 indexed citations

17.

Shaby, Benjamin A. & Brian J. Reich. (2012). Bayesian spatial extreme value analysis to assess the changing risk of concurrent high temperatures across large portions of European cropland. Environmetrics. 23(8). 638–648. 28 indexed citations

18.

Shaby, Benjamin A. & Daniel Fink. (2011). Embedding black-box regression techniques into hierarchical Bayesian models. Journal of Statistical Computation and Simulation. 82(12). 1753–1766. 2 indexed citations

19.

Miller, Jason, Montserrat Arrasate, Benjamin A. Shaby, et al.. (2010). Quantitative Relationships between Huntingtin Levels, Polyglutamine Length, Inclusion Body Formation, and Neuronal Death Provide Novel Insight into Huntington's Disease Molecular Pathogenesis. Journal of Neuroscience. 30(31). 10541–10550. 127 indexed citations

20.

Shaby, Benjamin A. & Christopher B. Field. (2006). Regression tools for CO<sub>2</sub> inversions: application of a shrinkage estimator to process attribution. Tellus B. 58(4). 279–279. 2 indexed citations

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.

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