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Encyclopedia of Mathematical Geosciences, 2012
In lieu of an abstract, here is the entry's first paragraph: Robust statistics are procedures that maintain nominal Type I error rates and statistical power in the presence of violations of the assumptions that underpin parametric inferential statistics.
Peter Filzmoser
semanticscholar +5 more sources
In lieu of an abstract, here is the entry's first paragraph: Robust statistics are procedures that maintain nominal Type I error rates and statistical power in the presence of violations of the assumptions that underpin parametric inferential statistics.
Peter Filzmoser
semanticscholar +5 more sources
Simulation optimization using stochastic kriging with robust statistics
Journal of the Operational Research Society, 2022Metamodels are widely used as fast surrogates to facilitate the optimization of simulation models. Stochastic kriging (SK) is an effective metamodeling tool for a mean response surface implied by stochastic simulation.
Linhan Ouyang +4 more
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Algorithmic High-Dimensional Robust Statistics
, 2023Robust statistics is the study of designing estimators that perform well even when the dataset significantly deviates from the idealized modeling assumptions, such as in the presence of model misspecification or adversarial outliers in the dataset.
Ilias Diakonikolas, D. Kane
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Ore Geology Reviews, 2019
Multivariate geochemical anomaly identification is one of the most important tasks in exploration geochemical data analysis. This paper proposes a new approach to identify multivariate geochemical anomalies which accounts for the degree of spatial ...
T. T. Nguyen, T. Vu
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Multivariate geochemical anomaly identification is one of the most important tasks in exploration geochemical data analysis. This paper proposes a new approach to identify multivariate geochemical anomalies which accounts for the degree of spatial ...
T. T. Nguyen, T. Vu
semanticscholar +1 more source
Distributionally Robust Optimization and Robust Statistics
Statistical ScienceWe review distributionally robust optimization (DRO), a principled approach for constructing statistical estimators that hedge against the impact of deviations in the expected loss between the training and deployment environments.
José H. Blanchet +3 more
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A Theoretical Review of Modern Robust Statistics
Annual Review of Statistics and Its ApplicationRobust statistics is a fairly mature field that dates back to the early 1960s, with many foundational concepts having been developed in the ensuing decades. However, the field has drawn a new surge of attention in the past decade, largely due to a desire
Po-Ling Loh
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