Robert E. Kass

35.1k total citations · 9 hit papers
158 papers, 23.8k citations indexed

About

Robert E. Kass is a scholar working on Cognitive Neuroscience, Statistics and Probability and Artificial Intelligence. According to data from OpenAlex, Robert E. Kass has authored 158 papers receiving a total of 23.8k indexed citations (citations by other indexed papers that have themselves been cited), including 67 papers in Cognitive Neuroscience, 46 papers in Statistics and Probability and 30 papers in Artificial Intelligence. Recurrent topics in Robert E. Kass's work include Neural dynamics and brain function (56 papers), Statistical Methods and Bayesian Inference (25 papers) and EEG and Brain-Computer Interfaces (17 papers). Robert E. Kass is often cited by papers focused on Neural dynamics and brain function (56 papers), Statistical Methods and Bayesian Inference (25 papers) and EEG and Brain-Computer Interfaces (17 papers). Robert E. Kass collaborates with scholars based in United States, Canada and New Zealand. Robert E. Kass's co-authors include Adrian E. Raftery, Larry Wasserman, Larry Wasserman, Emery N. Brown, Thomas J. DiCiccio, Valérie Ventura, D. J. Spiegelhalter, Partha P. Mitra, Michael J. Daniels and L. H. Wasserman and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and Journal of Geophysical Research Atmospheres.

In The Last Decade

Robert E. Kass

149 papers receiving 22.8k citations

Hit Papers

Bayes Factors 1985 2026 1998 2012 1995 1997 1995 1997 1995 2.5k 5.0k 7.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Bayes Factors
    1995 9.3k citations Robert E. Kass, Adrian E. Raftery Journal of the American Statistical Association profile →
  2. Computing Bayes Factors by Combining Simulation and Asymptotic Approximations
    1997 1.5k citations Thomas J. DiCiccio, Robert E. Kass et al. Journal of the American Statistical Association profile →
  3. Bayes Factors
    1995 1.4k citations Robert E. Kass, Adrian E. Raftery Journal of the American Statistical Association profile →
  4. Markov Chain Monte Carlo in Practice.
    1997 1.1k citations Robert E. Kass et al. Journal of the American Statistical Association profile →
  5. A Reference Bayesian Test for Nested Hypotheses and its Relationship to the Schwarz Criterion
    1995 816 citations Robert E. Kass et al. Journal of the American Statistical Association profile →
  6. The Selection of Prior Distributions by Formal Rules
    1996 733 citations Robert E. Kass, Larry Wasserman Journal of the American Statistical Association profile →
  7. Multiple neural spike train data analysis: state-of-the-art and future challenges
    2004 572 citations Robert E. Kass et al. profile →
  8. Numerical Methods for Unconstrained Optimization and Nonlinear Equations.
    1985 493 citations Robert E. Kass et al. Journal of the American Statistical Association profile →
  9. Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data
    2018 417 citations Pengcheng Zhou, Shanna L. Resendez et al. eLife profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Robert E. Kass United States 50 5.4k 4.8k 4.3k 2.1k 1.9k 158 23.8k
B. D. Ripley United Kingdom 48 3.5k 0.6× 2.9k 0.6× 5.8k 1.4× 3.2k 1.5× 2.6k 1.4× 168 50.8k
John W. Tukey United States 70 8.1k 1.5× 3.2k 0.7× 6.7k 1.6× 1.2k 0.6× 2.8k 1.5× 229 52.7k
Hirotugu Akaike Japan 33 4.3k 0.8× 2.6k 0.5× 5.5k 1.3× 3.1k 1.5× 4.0k 2.1× 80 51.7k
J. A. Nelder United Kingdom 48 9.4k 1.7× 1.4k 0.3× 5.5k 1.3× 2.9k 1.4× 3.1k 1.6× 153 55.9k
Eric‐Jan Wagenmakers Netherlands 83 3.2k 0.6× 14.6k 3.0× 3.2k 0.8× 511 0.2× 1.5k 0.8× 315 32.8k
William H. Press United States 60 1.2k 0.2× 2.0k 0.4× 4.5k 1.1× 1.1k 0.5× 1.3k 0.7× 183 74.4k
B. Efron United States 20 4.9k 0.9× 1.3k 0.3× 2.7k 0.6× 968 0.5× 2.2k 1.1× 31 23.1k
Ingram Olkin United States 69 6.7k 1.2× 2.0k 0.4× 2.5k 0.6× 981 0.5× 2.6k 1.3× 274 42.1k
Kurt Hornik Austria 61 1.5k 0.3× 1.3k 0.3× 11.9k 2.8× 1.1k 0.5× 2.0k 1.0× 269 39.7k
Bernhard Schölkopf Germany 96 2.9k 0.5× 5.1k 1.1× 31.3k 7.3× 1.1k 0.5× 860 0.4× 583 79.6k

Countries citing papers authored by Robert E. Kass

Since Specialization
Citations

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

Fields of papers citing papers by Robert E. Kass

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Robert E. Kass. 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 Robert E. Kass. The network helps show where Robert E. Kass may publish in the future.

Co-authorship network of co-authors of Robert E. Kass

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

All Works

20 of 20 papers shown
1.
Kass, Robert E., et al.. (2023). Identification of interacting neural populations: methods and statistical considerations. Journal of Neurophysiology. 130(3). 475–496. 1 indexed citations
2.
Klein, Natalie, et al.. (2020). TORUS GRAPHS FOR MULTIVARIATE PHASE COUPLING ANALYSISa. PubMed Central. 7 indexed citations
3.
Tarr, Michael J., et al.. (2019). Exploring spatiotemporal neural dynamics of the human visual cortex. Human Brain Mapping. 40(14). 4213–4238. 6 indexed citations
4.
Chen, Yu, et al.. (2018). Stability of point process spiking neuron models. Journal of Computational Neuroscience. 46(1). 19–32. 7 indexed citations
5.
Zhou, Pengcheng, Shanna L. Resendez, Jose Rodríguez-Romaguera, et al.. (2018). Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data. eLife. 7. 417 indexed citations breakdown →
6.
Daniels, Michael J. & Robert E. Kass. (2016). A NOTE ON FIRST-STAGE APPROXIMATION IN TWO-STAGE HIERARCHICAL MODELS*. 3 indexed citations
7.
Zhang, Qiong, John R. Anderson, & Robert E. Kass. (2015). Consistency in Brain Activation Predicts Success in Transfer.. Cognitive Science. 1 indexed citations
8.
Scott, James G., Ryan C. Kelly, Matthew A. Smith, Pengcheng Zhou, & Robert E. Kass. (2015). False Discovery Rate Regression: An Application to Neural Synchrony Detection in Primary Visual Cortex. Journal of the American Statistical Association. 110(510). 459–471. 46 indexed citations
9.
Kass, Robert E.. (2011). Statistical Inference: The Big Picture. Statistical Science. 26(1). 1–9. 49 indexed citations
10.
Jarosiewicz, Beata, Steven M. Chase, George W. Fraser, et al.. (2008). Functional network reorganization during learning in a brain-computer interface paradigm. Proceedings of the National Academy of Sciences. 105(49). 19486–19491. 220 indexed citations
11.
Wallstrom, Garrick, Robert E. Kass, Anita Miller, Jeffrey F. Cohn, & Nathan A. Fox. (2004). Automatic correction of ocular artifacts in the EEG: a comparison of regression-based and component-based methods. International Journal of Psychophysiology. 53(2). 105–119. 256 indexed citations
12.
Natarajan, Ranjini & Robert E. Kass. (2000). Reference Bayesian Methods for Generalized Linear Mixed Models. Journal of the American Statistical Association. 95(449). 227–237. 142 indexed citations
13.
Daniels, Michael J. & Robert E. Kass. (1999). Nonconjugate Bayesian Estimation of Covariance Matrices and its Use in Hierarchical Models. Journal of the American Statistical Association. 94(448). 1254–1263. 156 indexed citations
14.
Kass, Robert E., Bradley P. Carlin, Andrew Gelman, & Radford M. Neal. (1998). Markov Chain Monte Carlo in Practice: A Roundtable Discussion. The American Statistician. 52(2). 93–100. 434 indexed citations
15.
DiCiccio, Thomas J., Robert E. Kass, Adrian E. Raftery, & Larry Wasserman. (1997). Computing Bayes Factors by Combining Simulation and Asymptotic Approximations. Journal of the American Statistical Association. 92(439). 903–915. 1516 indexed citations breakdown →
16.
Kass, Robert E. & Larry Wasserman. (1996). The Selection of Prior Distributions by Formal Rules. Journal of the American Statistical Association. 91(435). 1343–1370. 733 indexed citations breakdown →
17.
Kass, Robert E. & Adrian E. Raftery. (1995). Bayes Factors. Journal of the American Statistical Association. 90(430). 773–795. 9294 indexed citations breakdown →
18.
Eddy, William F., et al.. (1987). Graduate Education in Computational Statistics. The American Statistician. 41(1). 60–64. 3 indexed citations
19.
Kass, Robert E.. (1984). Canonical Parameterizations and Zero Parameter-Effects Curvature. Journal of the Royal Statistical Society Series B (Statistical Methodology). 46(1). 86–92. 37 indexed citations
20.
Kass, Robert E.. (1982). A Comment on “Is Jeffreys a ‘Necessarist’?”. The American Statistician. 36(4). 390–391. 1 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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