The Theory Of Canonical Moments With Applications In Statistics Probability And Analysis
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The Theory of Canonical Moments with Applications in Statistics, Probability, and Analysis
Abweichend von dem in der Literatur üblichen Ansatz, wird die Momententheorie und ihre Anwendung hier aus dem Blickwinkel von Statistik, Wahrscheinlichkeitstheorie und Analysis betrachtet. Zweck des Buches ist aufzuzeigen, daß die kanonischen Momente ein sehr leistungsstarkes Instrument sind zur Bestimmung der optimalen Versuchsplanung, zur Berechnung der Hauptmerkmale der Random-Walk-Theorie und zur Behandlung wahrscheinlichkeits- und statistikspezifischer Momentproblematik. Die Themenauswahl erfolgte unter dem Gesichtspunkt, daß einerseits anwendungsorientierte Leser einen ausreichend großen Einblick gewinnen, um mit dieser Problematik ganz konkret arbeiten zu können und andererseits Theoretiker eine erschöpfende Darstellung des mathematischen Hintergrundes erhalten. (10/97)
Latent Curve Models
Author: Kenneth A. Bollen
language: en
Publisher: John Wiley & Sons
Release Date: 2006-01-03
An effective technique for data analysis in the social sciences The recent explosion in longitudinal data in the social sciences highlights the need for this timely publication. Latent Curve Models: A Structural Equation Perspective provides an effective technique to analyze latent curve models (LCMs). This type of data features random intercepts and slopes that permit each case in a sample to have a different trajectory over time. Furthermore, researchers can include variables to predict the parameters governing these trajectories. The authors synthesize a vast amount of research and findings and, at the same time, provide original results. The book analyzes LCMs from the perspective of structural equation models (SEMs) with latent variables. While the authors discuss simple regression-based procedures that are useful in the early stages of LCMs, most of the presentation uses SEMs as a driving tool. This cutting-edge work includes some of the authors' recent work on the autoregressive latent trajectory model, suggests new models for method factors in multiple indicators, discusses repeated latent variable models, and establishes the identification of a variety of LCMs. This text has been thoroughly class-tested and makes extensive use of pedagogical tools to aid readers in mastering and applying LCMs quickly and easily to their own data sets. Key features include: Chapter introductions and summaries that provide a quick overview of highlights Empirical examples provided throughout that allow readers to test their newly found knowledge and discover practical applications Conclusions at the end of each chapter that stress the essential points that readers need to understand for advancement to more sophisticated topics Extensive footnoting that points the way to the primary literature for more information on particular topics With its emphasis on modeling and the use of numerous examples, this is an excellent book for graduate courses in latent trajectory models as well as a supplemental text for courses in structural modeling. This book is an excellent aid and reference for researchers in quantitative social and behavioral sciences who need to analyze longitudinal data.
Combinatorial Methods in Discrete Distributions
Author: Charalambos A. Charalambides
language: en
Publisher: John Wiley & Sons
Release Date: 2005-06-24
A unique approach illustrating discrete distribution theory through combinatorial methods This book provides a unique approach by presenting combinatorial methods in tandem with discrete distribution theory. This method, particular to discreteness, allows readers to gain a deeper understanding of theory by using applications to solve problems. The author makes extensive use of the reduction approach to conditional distributions of independent random occupancy numbers, and provides excellent studies of occupancy and sequential occupancy distributions, convolutions of truncated discrete distributions, and compound and mixture distributions. Combinatorial Methods in Discrete Distributions begins with a brief presentation of set theory followed by basic counting principles. Fundamental principles of combinatorics, finite differences, and discrete probability are included to give readers the necessary foundation to the topics presented in the text. A thorough examination of the field is provided and features: Stirling numbers and generalized factorial coefficients Occupancy and sequential occupancy distributions n-fold convolutions of truncated distributions Compound and mixture distributions Thoroughly worked examples aid readers in understanding complex theory and discovering how theory can be applied to solve practical problems. An appendix with hints and answers to the exercises helps readers work through the more complex sections. Reference notes are provided at the end of each chapter, and an extensive bibliography offers readers a resource for additional information on specialized topics.