Finite mixture models have provided a mathematical-based approach in statistical modeling in a wide variety of random phenomena. FMM have been applied in astronomy, biology, genetic, medicine, psychiatry, economics, engineering and marketing, among many other fields in the biological, physical and social science. Kamps suggested a new theoretical approach, which is called generalized order statistics (GOS). This new model includes ordinary order statistics, sequential order statistics, progressive order statistics and record value. The main purpose of this book is to investigate the...

Most of the observable phenomena in the empirical sciences are of a multivariate nature. In financial studies, assets in stock markets are observed simultaneously and their joint development is analyzed to better understand general tendencies and to track indices. In medicine recorded observations of subjects in different locations are the basis of reliable diagnoses and medication. In quantitative marketing consumer preferences are collected in order to construct models of consumer behavior. The underlying theoretical structure of these and many other quantitative studies of applied sciences...

In Kamps (1995) generalized order statistics (GOS) have been introduced as a unifying theme for several models of ascendingly ordered random variables (rv's). Following Kamps, Burkschat et al. (2003) have introduced the concept of dual generalized order statistics (DGOS) to unify several models that produce ordered rv's. The main aim of this book is to study the limit joint distribution function (df) of any two statistics in a wide subclass of the GOS and DGOS models known as m-GOS and m-DGOS respectively. This subclass contains many important practical models such as ordinary order...