D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Mathematics D-index 52 Citations 10,246 198 World Ranking 475 National Ranking 6

Research.com Recognitions

Awards & Achievements

2012 - Fellow of the American Association for the Advancement of Science (AAAS)

2007 - Fellow of the American Statistical Association (ASA)

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Normal distribution
  • Algebra

Marc G. Genton mainly focuses on Statistics, Applied mathematics, Econometrics, Covariance and Covariance function. His Statistics study often links to related topics such as Selection. His research integrates issues of Skewness, Estimator and Monte Carlo method in his study of Applied mathematics.

His studies in Econometrics integrate themes in fields like Maximum likelihood, Probabilistic logic, Spatial analysis and Electricity. His Covariance study incorporates themes from Statistical hypothesis testing, Covariance matrix and Likelihood-ratio test. His study in Covariance function is interdisciplinary in nature, drawing from both F-test, Geostatistics, Mathematical optimization and Random field.

His most cited work include:

  • Covariance Tapering for Interpolation of Large Spatial Datasets (533 citations)
  • Skew-Elliptical Distributions and Their Applications : A Journey Beyond Normality (480 citations)
  • Classes of kernels for machine learning: a statistics perspective (472 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of study are Statistics, Applied mathematics, Estimator, Multivariate statistics and Covariance. His research combines Econometrics and Statistics. His Applied mathematics research includes elements of Skewness, Distribution and Joint probability distribution.

His Estimator research incorporates elements of Variogram, Mathematical optimization and Robustness. As part of the same scientific family, Marc G. Genton usually focuses on Multivariate statistics, concentrating on Artificial intelligence and intersecting with Machine learning. His work carried out in the field of Covariance brings together such families of science as Algorithm, Covariance matrix and Random field.

He most often published in these fields:

  • Statistics (28.49%)
  • Applied mathematics (24.46%)
  • Estimator (19.09%)

What were the highlights of his more recent work (between 2018-2021)?

  • Multivariate statistics (17.20%)
  • Algorithm (13.44%)
  • Covariance (15.86%)

In recent papers he was focusing on the following fields of study:

Marc G. Genton focuses on Multivariate statistics, Algorithm, Covariance, Statistics and Wind power. His biological study spans a wide range of topics, including Pattern recognition, Spatial dependence and Bayesian inference. The concepts of his Algorithm study are interwoven with issues in Maximum likelihood, Diagonal and Autoregressive model.

His work on Covariance function as part of general Covariance study is frequently connected to Space time, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. The study incorporates disciplines such as Series and Robustness in addition to Statistics. His Multivariate normal distribution research is multidisciplinary, incorporating perspectives in Monte Carlo method and Applied mathematics.

Between 2018 and 2021, his most popular works were:

  • Directional Outlyingness for Multivariate Functional Data (28 citations)
  • Full likelihood inference for max‐stable data (26 citations)
  • Bayesian modeling of air pollution extremes using nested multivariate max-stable processes. (18 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Normal distribution
  • Algebra

His primary areas of investigation include Algorithm, Multivariate statistics, Autoregressive model, Wind power and Covariance. His research in Algorithm intersects with topics in Representation, Hierarchical database model, Conditional probability distribution and T-model. The study of Statistics and Machine learning are components of his Multivariate statistics research.

His Autoregressive model study integrates concerns from other disciplines, such as Robust statistics, Estimator, Skewness, Principal component analysis and Least squares. Marc G. Genton combines subjects such as Generator and Environmental economics with his study of Wind power. Marc G. Genton has included themes like Function, Applied mathematics and Random field in his Covariance study.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Covariance Tapering for Interpolation of Large Spatial Datasets

Reinhard Furrer;Marc G Genton;Douglas Nychka.
Journal of Computational and Graphical Statistics (2006)

700 Citations

Classes of kernels for machine learning: a statistics perspective

Marc G. Genton.
international conference on artificial intelligence and statistics (2002)

674 Citations

Skew-Elliptical Distributions and Their Applications : A Journey Beyond Normality

Marc. G. Genton.
(2004)

667 Citations

Geostatistical Space-Time Models, Stationarity, Separability, and Full Symmetry

Tilmann Gneiting;Marc G. Genton;Peter Guttorp.
(2007)

357 Citations

On fundamental skew distributions

Reinaldo B. Arellano-Valle;Marc G. Genton.
Journal of Multivariate Analysis (2005)

338 Citations

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime-Switching Space-Time (RST) Method

Tilmann Gneiting;Kristin Larson;Kenneth Westrick;Marc G Genton.
Journal of the American Statistical Association (2004)

279 Citations

Highly Robust Variogram Estimation

Marc G. Genton.
Mathematical Geosciences (1998)

256 Citations

Robust Likelihood Methods Based on the Skew-t and Related Distributions

Adelchi Azzalini;Marc G. Genton;Marc G. Genton.
International Statistical Review (2008)

244 Citations

Short-Term Spatio-Temporal Wind Power Forecast in Robust Look-ahead Power System Dispatch

Le Xie;Yingzhong Gu;Xinxin Zhu;Marc G. Genton.
power and energy society general meeting (2014)

230 Citations

A unified view on skewed distributions arising from selections

Reinaldo Boris Arellano-Valle;Márcia D. Branco;Marc G. Genton.
Canadian Journal of Statistics-revue Canadienne De Statistique (2006)

209 Citations

Best Scientists Citing Marc G. Genton

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Geoffrey J. McLachlan

Geoffrey J. McLachlan

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Arjun K. Gupta

Arjun K. Gupta

Bowling Green State University

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Tilmann Gneiting

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Heidelberg Institute for Theoretical Studies

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Noel A Cressie

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Michael L. Stein

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University of Chicago

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Mark F. J. Steel

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Håvard Rue

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Anthony C. Davison

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Saralees Nadarajah

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Brian J. Reich

Brian J. Reich

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Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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