http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
1 online resource (XIII, 352 pages 122 illustrations, 37 illustrations in color.)
This volume gathers peer-reviewed contributions that address a wide range of recent developments in the methodology and applications of data analysis and classification tools in micro and macroeconomic problems. The papers were originally presented at the 29th Conference of the Section on Classification and Data Analysis of the Polish Statistical Association, SKAD 2020, held in Sopot, Poland, September 7-9, 2020. Providing a balance between methodological contributions and empirical papers, the book is divided into five parts focusing on methodology, finance, economics, social issues and applications dealing with COVID-19 data. It is aimed at a wide audience, including researchers at universities and research institutions, graduate and doctoral students, practitioners, data scientists and employees in public statistical institutions.
Part 1: Methodology -- Chapter 1 - Evaluation of Two-Step Spectral Clustering Algorithm for Large Untypical Data Sets (Andrzej Dudek) -- Chapter 2 - Determining the Number of Groups in Cluster Analysis Using Classical Indexes and Stability Measures - Comparison of Results (Dorota Rozmus) -- Chapter 3 - Identification of the Words Most Frequently Used by Different Generations of Twitter Users (Agata Majkowska, Kamila Migdał-Najman, Krzysztof Najman and Katarzyna Raca) -- Chapter 4 - Classification Algorithms Applications for Information Security on the Internet: a Review (Michał Bryś) -- Chapter 5 - Outlier Detection with the Use of Isolation Forests (Krzysztof Najman and Krystian Zieliński) -- Part 2: Application in Finance -- Chapter 6 - Propositions of Transformations of Asymmetrical Nominants into Stimulants on the Example of Chosen Financial Ratios ( Barbara Batóg and Katarzyna Wawrzyniak) -- Chapter 7 - Gini Regression in The Capital Investment Risk Assessment - Sensitivity Risk Measures in Portfolio Analysis (Grażyna Trzpiot) -- Part 3: Application in Economics -- Chapter 8 - Enterprise Dark Data (Katarzyna Raca) -- Chapter 9 - The Significance of Medical Science Issues in Research Papers Published in the Field of Economics (Urszula Cieraszewska, Monika Hamerska, Paweł Lula and Marcela Zembura) -- Chapter 10 - Application of Duration Analysis Methods in the Study of the Exit of a Real Estate Sale Offer from the Offer Database System (Ewa Putek-Szeląg, Anna Gdakowicz) -- Chapter 11 - Is Society Ready for Long-Term Investments? - Profiles of Electricity Users in Silesia (Sylwia Słupik and Joanna Trzęsiok) -- Chapter 12 - The Use of the Spatial Taxonomic Measure of Development to Assess the Tourist Attractiveness of Districts of the Lesser Poland Province(Jacek Wolak) -- Part 4: Application in Social Issues -- Chapter 13 - Models of Competing Events in Assessing the Effects of the Transition of Unemployed People Between the States of Registration and De-registration (Beata Bieszk-Stolorz) -- chapter 14 - Direct Adjusted Survival Probabilities in the Analysis of Finding a Job by the Unemployed Depending on Their Individual Characteristics(Wioletta Grzenda) -- Chapter 15 - Europe 2020 Strategy - Objective Evaluation of Realization and Subjective Assessment by Seniors as Beneficiaries of Social Assumptions (Klaudia Przybysz, Agnieszka Stanimir and Marta Wasiak) -- Chapter 16 - Do Seniors Get to the Disco by Bike or in a Taxi? - Classification of Seniors According to Their Preferred Means of Transport (Joanna Kos-Łabędowicz and Joanna Trzęsiok) -- Part 5: Application with COVID-19 Data -- Chapter 17 - The Impact of the COVID-19 Pandemic on the Economies of European Countries in the Period January-September 2020 Based on Economic Indicators (Ewelina Nojszewska and Agata Sielska) -- Chapter 18 - Modelling the Risk of Foreign Divestment in the Visegrad Group Countries During the COVID-19 Pandemic (Marcin Salamaga) -- Chapter 19 - Analysis of COVID-19 Dynamics in EU Countries Using the Dynamic Time Warping Method and ARIMA Models (Joanna Landmesser).
edited by Krzysztof Jajuga, Krzysztof Najman, Marek Walesiak.
Statistics for Business, Management, Economics, Finance, Insurance
Statistics for Social Sciences, Humanities, Law
Studies in Classification, Data Analysis, and Knowledge Organization