David E. Tyler

4.6k total citations · 1 hit paper
63 papers, 2.6k citations indexed

About

David E. Tyler is a scholar working on Statistics and Probability, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, David E. Tyler has authored 63 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Statistics and Probability, 12 papers in Artificial Intelligence and 7 papers in Statistics, Probability and Uncertainty. Recurrent topics in David E. Tyler's work include Advanced Statistical Methods and Models (39 papers), Statistical Methods and Inference (20 papers) and Statistical Methods and Bayesian Inference (12 papers). David E. Tyler is often cited by papers focused on Advanced Statistical Methods and Models (39 papers), Statistical Methods and Inference (20 papers) and Statistical Methods and Bayesian Inference (12 papers). David E. Tyler collaborates with scholars based in United States, Finland and Netherlands. David E. Tyler's co-authors include John T. Kent, Esa Ollila, Visa Koivunen, H. Vincent Poor, Kay Tatsuoka, Hannu Oja, Lutz Dümbgen, Morris L. Eaton, David S. Stoffer and Klaus Nordhausen and has published in prestigious journals such as Journal of the American Statistical Association, IEEE Transactions on Signal Processing and Biometrika.

In The Last Decade

David E. Tyler

62 papers receiving 2.4k citations

Hit Papers

Complex Elliptically Symmetric Distributions: Survey, New... 2012 2026 2016 2021 2012 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David E. Tyler United States 26 1.5k 492 483 402 367 63 2.6k
Esa Ollila Finland 23 421 0.3× 872 1.8× 347 0.7× 456 1.1× 77 0.2× 93 1.8k
C. G. Khatri India 22 1.2k 0.8× 213 0.4× 473 1.0× 175 0.4× 165 0.4× 110 2.6k
Ronald W. Butler United States 19 792 0.5× 99 0.2× 356 0.7× 206 0.5× 257 0.7× 83 1.6k
E. Masry United States 22 378 0.2× 306 0.6× 370 0.8× 132 0.3× 76 0.2× 66 1.7k
Bernard Delyon France 18 413 0.3× 148 0.3× 1.0k 2.2× 65 0.2× 166 0.5× 59 3.3k
Morris L. Eaton United States 22 1.2k 0.8× 94 0.2× 536 1.1× 56 0.1× 270 0.7× 71 2.3k
Richard A. Redner United States 14 582 0.4× 320 0.7× 1.1k 2.4× 74 0.2× 85 0.2× 25 2.4k
Bharath K. Sriperumbudur United States 19 593 0.4× 191 0.4× 1.2k 2.4× 79 0.2× 154 0.4× 50 2.5k
Wei Biao Wu United States 30 1.6k 1.0× 203 0.4× 516 1.1× 32 0.1× 158 0.4× 158 3.2k
Ayanendranath Basu India 17 1.2k 0.8× 237 0.5× 301 0.6× 35 0.1× 432 1.2× 97 1.8k

Countries citing papers authored by David E. Tyler

Since Specialization
Citations

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

Fields of papers citing papers by David E. Tyler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David E. Tyler

This figure shows the co-authorship network connecting the top 25 collaborators of David E. Tyler. A scholar is included among the top collaborators of David E. Tyler 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 David E. Tyler. David E. Tyler 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.
Ollila, Esa, et al.. (2021). On the variability of the sample covariance matrix under complex elliptical distributions. arXiv (Cornell University). 3 indexed citations
2.
Tyler, David E., et al.. (2015). On the eigenvalues of the spatial sign covariance matrix in more than\n two dimensions. arXiv (Cornell University). 9 indexed citations
3.
Vogel, Daniel, et al.. (2014). The spatial sign covariance matrix with unknown location. Journal of Multivariate Analysis. 130. 107–117. 13 indexed citations
4.
Boente, Graciela, Matías Salibián‐Barrera, & David E. Tyler. (2014). A characterization of elliptical distributions and some optimality properties of principal components for functional data. Journal of Multivariate Analysis. 131. 254–264. 21 indexed citations
5.
Tyler, David E., et al.. (2014). The asymptotic inadmissibility of the spatial sign covariance matrix for elliptically symmetric distributions. Biometrika. 101(3). 673–688. 15 indexed citations
6.
Vogel, Daniel & David E. Tyler. (2014). Robust estimators for nondecomposable elliptical graphical models. Biometrika. 101(4). 865–882. 2 indexed citations
7.
Ollila, Esa, David E. Tyler, Visa Koivunen, & H. Vincent Poor. (2012). Compound-Gaussian Clutter Modeling With an Inverse Gaussian Texture Distribution. IEEE Signal Processing Letters. 19(12). 876–879. 118 indexed citations
8.
Tyler, David E.. (2008). Robust Statistics: Theory and Methods. Ricardo A. Maronna, R. Douglas Martin, and Victor J. Yohai. RePEc: Research Papers in Economics. 103. 888–889. 1 indexed citations
9.
Chen, Zhiqiang & David E. Tyler. (2003). On the behavior of Tukey's depth and median under symmetric stable distributions. Journal of Statistical Planning and Inference. 122(1-2). 111–124. 5 indexed citations
10.
Comaniciu, Dorin, Peter Meer, Kun Xu, & David E. Tyler. (2003). Retrieval performance improvement through low rank corrections. 50–54. 6 indexed citations
11.
Chen, Zhiqiang & David E. Tyler. (2002). The influence function and maximum bias of Tukey's median. The Annals of Statistics. 30(6). 17 indexed citations
12.
Kent, John T. & David E. Tyler. (2001). Regularity and Uniqueness for Constrained M-Estimates and Redescending M-Estimates. The Annals of Statistics. 29(1). 10 indexed citations
13.
Kent, John T. & David E. Tyler. (1996). Constrained M-estimation for multivariate location and scatter. The Annals of Statistics. 24(3). 73 indexed citations
14.
Kent, John T., et al.. (1994). A curious likelihood identity for the multivariate t-distribution. Communications in Statistics - Simulation and Computation. 23(2). 441–453. 58 indexed citations
15.
Eaton, M. L. & David E. Tyler. (1994). The Asymptotic Distribution of Singular-Values with Applications to Canonical Correlations and Correspondence Analysis. Journal of Multivariate Analysis. 50(2). 238–264. 50 indexed citations
16.
Stoffer, David S., David E. Tyler, & Andrew McDougall. (1993). Spectral analysis for categorical time series: Scaling and the spectral envelope. Biometrika. 80(3). 611–622. 54 indexed citations
17.
Tyler, David E.. (1983). The Asymptotic Distribution of Principal Component Roots Under Local Alternatives to Multiple Roots. The Annals of Statistics. 11(4). 14 indexed citations
18.
Tyler, David E.. (1983). Robustness and efficiency properties of scatter matrices. Biometrika. 70(2). 411–420. 125 indexed citations
19.
Tyler, David E.. (1982). Radial estimates and the test for sphericity. Biometrika. 69(2). 429–436. 68 indexed citations
20.
Tyler, David E.. (1981). Asymptotic Inference for Eigenvectors. The Annals of Statistics. 9(4). 106 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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