This book provides new theories, applications and quantitative methods in demography, population studies and statistics. It presents and applies data analysis, statistics and stochastic modeling techniques focusing on demography, population aging, mortality and health sciences. The book describes diverse stochastic processes as well as Markov and semi-Markov models in demography and population studies, along with chapters on statistical models and methods in biostatistics and epidemiology. As such the book will be a valuable source to demographers, health scientists, statisticians, economists and sociologists.
Preface.- PART
1. Demography and Related Applications: Health Status and
the Lifespan Limit:
Chapter 1 The Health Status of a Population Estimated:
The History of Health State Curves: Christos H Skiadas and Charilaos
Skiadas.
Chapter 2 Remarks on Limits to Human Lifespan: Christos H
Skiadas.
Chapter 3 Exploring the Health Status of a Population: A Simple
Health State Model vs the Gompertz Model: Christos H Skiadas.
Chapter 4
Estimation of the healthy life expectancy in Italy through a simple model
based on mortality rate: Christos Skiadas and Maria Felice Arezzo.- PART
2.
Mortality Modeling and Applications:
Chapter 5 Using Child, Adult, and
Old-age Mortality to Establish a Developing Countries Mortality Database
(DMD): Nan Li, Hong Mi and Patrick Gerland.
Chapter 6 A method for the
evaluation of Health trends in Greece, 1961-2013: Konstantinos N. Zafeiris
and Christos H. Skiadas.
Chapter 7 A method for the forecasting of
mortality: Konstantinos N. Zafeiris.
Chapter 8 Prospective scenarios on
coverage of deaths in Brazil: Neir Antunes Paes, and Alisson dos Santos
Silva.- PART
3. Statistical Models and Methods in Biostatistics and
Epidemiology:Chapter 9 Applications of the Cumulative Rate to Kidney Cancer
Statistics in Australia: Janelle Brennan, K.C. Chan, Rebecca Kippen, C.T.
Lenard, T.M. Mills, and Ruth F.G. Williams.
Chapter 10 To Reliability of
Mortality Shifts in Working Population in Russia: Alla Ivanova, Tamara
Sabgaida, Viktoria Semyonova, Elena Zemlyanova.
Chapter 11 Three-way data
analysis applied to cause specific mortality trends: Giuseppe Giordano,
Steven Haberman, Maria Russolillo.- PART
4. Stochastic and Neuro-Fuzzy
Methods:Chapter 12 Measuring Latent Variables is space and/or time: A Gender
Statistics exercise: Gaia Bertarelli, Franca Crippa, and Fulvia Mecatti.-
Chapter 13 Stochastic Distance between Burkitt Lymphoma/Leukemia Strains:
Jesśs E. Garcķa, R. Gholizadeh, and V.A. Gonzįlez-López.
Chapter 14 Monte
Carlo Methods Applied in Health Research: Pereira JA, Mendes L, Costa A,
Oliveira TA.
Chapter 15 A neuro-fuzzy approach to measuring attitudes: Maria
Symeonaki, Aggeliki Kazani and C. Michalopoulou.- PART
5. Data Analysis in
Demography:Chapter 16 Differences in Life Expectancy by Marital Status in the
Czech Republic after 1990 and their Decomposition by Age: Tomas Fiala and
Jitka Langhamrovį.
Chapter 17 Air pollution and health risks: a statistical
analysis aiming at improving air quality in an alpine Italian province:
Giuliana Passamani, Matteo Tomaselli.
Chapter 18 AR Dynamic Evolving
Neuro-Fuzzy Inference System for Mortality Data: Gabriella Piscopo.
Chapter
19 Empirical Power Study of the Jackson Exponentiality Test: Frederico Caeiro
and Ayana Mateus.
Chapter 20 An intervention analysis regarding the impact
of the introduction of budget airline routes to Maltese tourism demographics:
Maristelle Darmanin and David Suda.
Chapter 21 Investigating Southern
Europeans Perceptions of Their Employment Status: Aggeliki Yfanti, Catherine
Michalopoulou, Aggelos Mimis, and Stelios Zachariou.- PART
6. Health
Sciences, Demography, Risk and Insurance:
Chapter 22 Risk factors of Severe
Cognitive Impairment in the Czech Republic: Kornélia Cséfalvaiovį and Jitka
Langhamrovį.
Chapter 23 On the Measurement of Early Job Insecurity in
Europe: Maria Symeonaki, Glykeria Stamatopoulou and Maria Karamessini.-
Chapter 24 Health estimates for some countries of the rapid developing world:
Konstantinos N. Zafeiris and Christos H. Skiadas.
Chapter 25 Social capital,
income inequality and the health of the elderly: Maria Felice Arezzo.-
Chapter 26 Life annuity portfolios: risk-adjusted valuations and suggestions
on the product attractiveness: Valeria D'Amato, Emilia Di Lorenzo, Albina
Orlando, and Marilena Sibillo.
Chapter 27 Flexible retirement scheme for the
Italian mortality experience: Mariarosaria Coppola, Maria Russolillo, and
Rosaria Simone.
Chapter 28 Sibling Death Clustering among the Tribes of
Central and Eastern India: An Application of Random Effects Probit Model:
Laxmi Kant Dwivedi , Mukesh Ranjan.
Christos H. Skiadas, PhD, was the founder and director of the Data Analysis and Forecasting Laboratory at the Technical University of Crete. 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 18 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 an associate professor in mathematics and computer science at Hanover College. 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 state modeling.
