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High-dimensional Data in Economics and their (Robust) Analysis
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SYSNO ASEP 0473577 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title High-dimensional Data in Economics and their (Robust) Analysis Author(s) Kalina, Jan (UIVT-O) RID, SAI, ORCID Source Title Serbian Journal of Management. - : Univerzitet u Beogradu - ISSN 1452-4864
Roč. 12, č. 1 (2017), s. 171-183Number of pages 13 s. Language eng - English Country RS - Serbia Keywords econometrics ; high-dimensional data ; dimensionality reduction ; linear regression ; classification analysis ; robustness Subject RIV BB - Applied Statistics, Operational Research OECD category Statistics and probability R&D Projects GA17-07384S GA ČR - Czech Science Foundation (CSF) Institutional support UIVT-O - RVO:67985807 UT WOS 000443474000012 EID SCOPUS 85018191894 DOI 10.5937/sjm12-10778 Annotation This work is devoted to statistical methods for the analysis of economic data with a large number of variables. The authors present a review of references documenting that such data are more and more commonly available in various theoretical and applied economic problems and their analysis can be hardly performed with standard econometric methods. The paper is focused on highdimensional data, which have a small number of observations, and gives an overview of recently proposed methods for their analysis in the context of econometrics, particularly in the areas of dimensionality reduction, linear regression and classification analysis. Further, the performance of various methods is illustrated on a publicly available benchmark data set on credit scoring. In comparison with other authors, robust methods designed to be insensitive to the presence of outlying measurements are also used. Their strength is revealed after adding an artificial contamination by noise to the original data. In addition, the performance of various methods for a prior dimensionality reduction of the data is compared. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2018
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