Titlebook: Data Science for Financial Econometrics; Nguyen Ngoc Thach,Vladik Kreinovich,Nguyen Duc Tru Book 2021 The Editor(s) (if applicable) and Th

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J. S. Shang,P. G. Huang,D. B. Paultheory-based or ‘rigorous’ lasso of Bickel et al. (.), Belloni et al. (.), Belloni and Chernozhukov (.), Belloni et al. (.) and recently extended to the case of dependent data by Chernozhukov et al. (.), where the lasso penalty level is derived on theoretical grounds. The rigorous lasso has appealin

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Andreas Richter,Jörg Stiller,Roger Grundmannsed. In such situations, a reasonable idea is to take into account that the values of the corresponding parameters should not be too large; this idea is known as regularization. Several different regularization techniques have been proposed; empirically the most successful are LASSO method, when we

Entirety

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https://doi.org/10.1007/978-3-642-01273-0 intrinsic quality of data, including accuracy and completeness, the qualities of information content such as relevance, trust and understandability, as well as the explainable character of the data mining tool extracting information from data. We focus on fuzzy-set based contributions to these aspe

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Andreas Richter,Jörg Stiller,Roger Grundmann their parametric posterior distributions is much greater than the predictive uncertainty of new (unknown) observables. Consequently, when model results are reported, uncertainty in the observable should be reported and not uncertainty in the parameters of these models. If someone mistook the uncert

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Computational Fluid Dynamics 2010m variables. In this short contribution, we briefly review three approaches to such comparison: (i) .: an approach based on a pointwise comparison of cumulative distribution functions; (ii) .: an approach based on a pairwise comparison in terms of winning probabilities; (iii) .: an approach based on

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Alexey N. Volkov,Gerard M. O’Connorable probabilistic fallacies that underpin investor behaviour and the consequent deviation of asset prices from the rational expectations equilibrium. In real financial markets, the complexity of financial products and the surrounding ambiguity calls for a more general formalization of agents belief

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Alexey N. Volkov,Gerard M. O’Connord APP equations provide the necessary sample size to meet specifications. Thus far, APP articles have mostly focused on the results of true experiments, where it is possible to randomly assign participants to conditions designed to create variance. But researchers in fields such as education and psy

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