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BeamNet: Unsupervised Beamforming for ISAC Systems Under Imperfect CSI. [PDF]
Entropy (Basel)Nimnaka H +4 more
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Robust statistical arbitrage strategies
Quantitative Finance, 2019We investigate statistical arbitrage strategies when there is ambiguity about the underlying time-discrete financial model. Pricing measures are assumed to be martingale measures calibrated to prices of liquidly traded options, whereas the set of admissible physical measures is not necessarily implied from market data.
Eva Lütkebohmert, Julian Sester
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Robust statistical inference for matched win statistics
Statistical Methods in Medical Research, 2022As alternatives to the time-to-first-event analysis of composite endpoints, the win statistics, that is, the net benefit, the win ratio, and the win odds have been proposed to assess treatment effects, using a hierarchy of prioritized component outcomes based on clinical relevance or severity. Whether we are using paired organs of a human body or pair-
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Proceedings of the 19th International Conference on Evaluation and Assessment in Software Engineering, 2015
This keynote discusses the need for more robust statistical methods. For visualizing data I suggest using Kernel density plots rather than box plots. For parametric analysis, I propose more robust measures of central location such as trimmed means, which can support reliable tests of the differences between the central location of two or more samples ...
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This keynote discusses the need for more robust statistical methods. For visualizing data I suggest using Kernel density plots rather than box plots. For parametric analysis, I propose more robust measures of central location such as trimmed means, which can support reliable tests of the differences between the central location of two or more samples ...
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Journal of the American Statistical Association, 1983
Leone Y. Low, Peter J. Huber
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Leone Y. Low, Peter J. Huber
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2013
“Robust” estimators are resistant to outliers in data, contrary to the usual classical least-squares estimator such as NLSE. We will describe two robust estimators in this chapter and give an example of the application of them to pre-processing some experimental data.
Harold A. Sabbagh +4 more
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“Robust” estimators are resistant to outliers in data, contrary to the usual classical least-squares estimator such as NLSE. We will describe two robust estimators in this chapter and give an example of the application of them to pre-processing some experimental data.
Harold A. Sabbagh +4 more
openaire +1 more source