Quantitative Methods and Data Analysis in Applied Demography - Volume 2

Zusatztext

This second volume of two complements volume 1 by discussing models, risk and surveys in applied demography. Models and modeling cover a wide range of data analysis methods and techniques to cope with demographic data including principal components, clustering, GARCH models and dynamic correlation, multilevel models and stochastic insurance models including an R package for clustering as well. Surveys cope with the analysis of various data set arising in National and International context. Data from European Social Survey and National surveys are analyzed, as well as food waste generation analysis and social mobility in Europe along with post Covid-19 data sets. By providing a methodology to cope with health and mortality problems in demography and society in Volume 1 and quantifying important health parameters in Volume 2, the books are a valuable guide for applied demographers, researchers, theoreticians, and practitioners from various disciplines and especiallyhealth scientists, statisticians, economists, and sociologists.

Autorenportrait

Christos H. Skiadas, PhD, was the founder and director of the Data Analysis and Forecasting Laboratory at the Technical University of Crete and former Vice-Rector of the University. He is chair of the Demographics Workshop series, the Applied Stochastic Models and Data Analysis Conference series and the Chaotic Modeling and Simulation Conference series. He has published more than 80 papers, three monographs, and 24 books, including probability, statistics, data analysis and forecasting. His research interests include innovation diffusion modeling and forecasting, life table data modeling, healthy life expectancy estimates, and deterministic, stochastic, and chaotic modeling. Charilaos Skiadas, PhD, is professor in mathematics and computer science at Hanover College, Indiana, USA. His research interests encompass a wide array of mathematical and computing topics, ranging from algebraic geometry to statistics and programming languages to data science and health statemodeling.

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