To browse Academia. Rivista italiana di economia, demografia Extrem Strip Poker Vk statistica. Psychiatry: Interpersonal and Biological Processes, Anesthesia Topics for Plastic and Reconstructive Surgery, Developing Technology Mediation in Learning Environments, Discourse: Studies in the Extrem Strip Poker Vk Politics of Education, Log in with Facebook Log in with Google. Remember me on this computer. Enter the email address you signed up with and we'll email you a reset link. Need an account? Click here to sign up. All rights are reserved, whether the whole or part of the material is concerned. Nothing from this publication may be translated, reproduced, stored in a computerized system or published in any form or in any manner. The publisher is not responsible for possible damages, which could be a result of content derived from this publication. The Symposium provides the ideal opportunity to bring together academicians who work in this field, data scientists, data miners, data engineers and researchers who want to improve themselves. The main goal of this event is to provide an international scientific forum for the exchange of new ideas in data science fields. With the increase of global competition and the development of technology, the training of experts in this field Extrem Strip Poker Vk importance with the studies carried out in the field of data science and engineering. Data discipline and engineering discipline have emerged to give meaning to data stacks, to analyze data stacks and to transform them into information. The implementation of data science and engineering methods enables administrators to make effective and quick decisions to increase operational efficiency as well as to keep the pulse of the society, employees and institutions. I would like to thank the program committee members for their support at shaping the Symposium program and the research community for their valuable contributions to the Symposium. With my warmest regards and respect, Prof. With a Note on Ability and Disability The paper developed algorithms for implementation of linear regression for estimating CVaR as a function of some factors. Such regression is called CVaR Superquantile regression. The main statement of the paper: CVaR linear regression can be reduced to minimizing the Rockafellar Error function with linear programming. The theoretical basis for the analysis is established with the Quadrangle Theory of risk functions. We derived relationships between elements of CVaR Quadrangle and Mixed-Quantile Quadrangle for discrete distributions with equally probable atoms. We presented two equivalent variants of discretization of this integral, which resulted in two sets of parameters for the Mixed-Quantile Quadrangle. Alternatively, a two-stage procedure based on Decomposition Theorem can be used for CVaR linear regression with both sets of parameters. We illustrated theoretical results with a case study demonstrating the numerical efficiency of the suggested approach. The case study codes, data and results are posted at the website. American Economic Review 7— Empirical Economics 26, Journal of Finance 52, Uryasev Journal of Risk. Bassett : Regression Quantiles, Econometrica 46, 33—
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