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＜電子ブック＞
Classification and Data Analysis : Theory and Applications / edited by Krzysztof Jajuga, Jacek Batóg, Marek Walesiak
(Studies in Classification, Data Analysis, and Knowledge Organization. ISSN:21983321)

版	1st ed. 2020.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2020
本文言語	英語
大きさ	XIII, 335 p. 110 illus., 45 illus. in color : online resource
著者標目	Jajuga, Krzysztof editor Batóg, Jacek editor Walesiak, Marek editor SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Data mining LCSH:Social sciences -- Statistical methods  全ての件名で検索 LCSH:Econometrics LCSH:Mathematical statistics -- Data processing  全ての件名で検索 FREE:Statistics in Business, Management, Economics, Finance, Insurance FREE:Data Mining and Knowledge Discovery FREE:Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy FREE:Statistical Theory and Methods FREE:Quantitative Economics FREE:Statistics and Computing
一般注記	Preface -- Methods -- Comparison of proposals of transformation of nominants into stimulants on the example of financial ratios of companies listed on the Warsaw Stock Exchange -- Silhouette index as clustering evaluation tool -- The Role of Discretization of Continuous Variables in SocioEconomic Classification Models on the Example of Logistic Regression Models and Artificial Neural Networks -- Intuitionistic fuzzy synthetic measure for ordinal data -- Improving Classification Accuracy of Ensemble Learning for Symbolic Data Trough Neural Networks’ Feature Extraction -- Applications in Finance -- Inequality restricted least squares (IRLS) model of real estate prices -- Application of Hill estimator to assess extreme risks in the metals market -- Segmentation of Enterprises on the Basis of Their Duration Using Survival Trees. Results of an Analysis for Legal Persons and Organizational Entities without Legal Personality in the Łódzkie Voivodship -- Corporate Bankruptcy Prediction with the Use of the Logit Leaf Model -- The impact of longevity on a valuation of long-term investments returns: the case of selected European countries -- Applications in Economics.-Sustainable Development and Green Economy in the European Union Countries – statistical analysis -- The review of indicators of data quality in intra-Community trade in goods. The choice of an indicator and its effect on the ranking of countries -- Development of ICT in Poland in Comparison with the European Union Countries – Multivariate Statistical Analysis -- Sensitivity Analysis in Causal Mediation Effects for TAM Model -- Applications in Social Problems -- Prentice-Williams-Peterson models in the assessment of the influence of the characteristics of the unemployed on the intensity of subsequent registrations in the labour office -- Right-skewed distribution of features and the identification problem of the financial autonomy of local administrative units -- Multi-Criteria Rankings with Interdependent Criteria: Case of EU Countries on Their Way to Healthy Lives and Well-Being -- The comparison of income distributions for women and men in the European Union countries -- Common stochastic mortality trends for multiple European populations -- Impact of the selected factors on the men and women wages in Poland in 2014. The conjoint analysis application This volume gathers peer-reviewed contributions on data analysis, classification and related areas presented at the 28th Conference of the Section on Classification and Data Analysis of the Polish Statistical Association, SKAD 2019, held in Szczecin, Poland, on September 18–20, 2019. Providing a balance between theoretical and methodological contributions and empirical papers, it covers a broad variety of topics, ranging from multivariate data analysis, classification and regression, symbolic (and other) data analysis, visualization, data mining, and computer methods to composite measures, and numerous applications of data analysis methods in economics, finance and other social sciences. The book is intended for a wide audience, including researchers at universities and research institutions, graduate and doctoral students, practitioners, data scientists and employees in public statistical institutions HTTP:URL=https://doi.org/10.1007/978-3-030-52348-0

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