Complex Data Modeling and Computationally Intensive Statistical Methods

Demography is the study by statistical methods of human populants involving the measurement of their size, growth and diminution, the proportions living within some areas, being born, marrying, having children or dying and the related functions of fertility, nuptially and morality. This book begins by defining a number of concepts which are useful for demographic analysis, including the significant events in life and types of statistical data which are collected, published and used. It then describes the various kinds of change which can occur and the underlying causes - social, economic and political. The central section provides an account of the history of population growth and development, and of the situation on an international and national scale. Resources available for the support of mankind and their relationship with living standards are explored. The politics of population and the prospects for the future are also described.

Suitable for a one or two semester course, this book takes a practical approach to methods of statistical modeling and data analysis that are most often used in scientific work.

This book provides the mathematical foundations of statistics. Its aim is to explain the principles, to prove the formulae to give validity to the methods employed in the interpretation of statistical data. Many examples are included but, since the primary emphasis is on the underlying theory, it is of interest to students of a wide variety of subjects: biology, psychology, agriculture, economics, physics, chemistry, and (of course) mathematics.

Integrated Population Biology and Modeling: Part B, Volume 40 offers very delicately complex and precise realities of quantifying modern and traditional methods of understanding populations and popula

This book provides the most comprehensive treatment to date of microeconometrics, the analysis of individual-level data on the economic behavior of individuals or firms using regression methods for cross section and panel data. The book is oriented to the practitioner. A basic understanding of the linear regression model with matrix algebra is assumed. The text can be used for a microeconometrics course, typically a second-year economics PhD course; for data-oriented applied microeconometrics field courses; and as a reference work for graduate students and applied researchers who wish to fill in gaps in their toolkit. Distinguishing features of the book include emphasis on nonlinear models and robust inference, simulation-based estimation, and problems of complex survey data. The book makes frequent use of numerical examples based on generated data to illustrate the key models and methods. More substantially, it systematically integrates into the text empirical illustrations based on s

The third edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish betw

Become a master of data analysis, modeling, and spreadsheet use with BUSINESS ANALYTICS: DATA ANALYSIS AND DECISION MAKING, 6E! This popular quantitative methods text helps you maximize your success w

The book is an introduction to the methods that deal with problems raised in using multiscale mathematical/statistical models such as wavelets and other multiscale systems. Special emphasis is given t

Design structure matrix (DSM) is a straightforward and flexible modeling techniquethat can be used for designing, developing, and managing complex systems. DSM offers networkmodeling tools that repres

The goal of this book is to provide an overview of statistical models and methods that are useful in the analysis of longitudinal data; that is, data in the form of repeated measurements on the same e

Consulting engineer Moss describes methods for analyzing reliability data, from simply calculating failure rates and using histograms to using more complex analyses based on models. He presents the fu

With an emphasis on experimental design and sampling, The Analysis of Ecological Data Using R presents all of the necessary statistical methods along with the ecological background for each problem. E

Multistate Models for the Analysis of Life History Data provides the first comprehensive treatment of multistate modeling and analysis, including parametric, nonparametric and semiparametric methods a

Practical Methods for Analysis and Design of HV Installation Grounding Systems gives readers a basic understanding of the modeling characteristics of the major components of a complex grounding system

Advanced Issues in Partial Least Squares Structural Equation Modeling provides a practical and applied description of advanced issues in PLS-SEM relevant for students, professors and applied researchers. Authors Joseph F. Hair, Jr., Marko Sarstedt, Christian Ringle, Siegfried P. Gudergan combine simple explanations of complex statistical concepts with examples and case studies that readers can follow using datasets available with the book. Furthermore, instead of providing technical descriptions of the concepts with a multitude of formulae, the book will focus on the appropriate analysis of data and interpretation of outputs. Many of the examples are based on the SmartPLS software, created and maintained by the authors. The book is easy to use for both independent and guided learning, including numerous graphs, tables, illustrations, multiple downloadable datasets (provided on a companion website), exercises, and further readings. Where appropriate, supplementary analyses and data mana

As the study of environmental policy and justice becomes increasingly significant in today’s global climate, standard statistical approaches to gathering data have become less helpful at generating ne

Simulation modeling is increasingly integrated into research and policy analysis of complex sociotechnical systems in a variety of domains. Model-based analysis and policy design inform a range of app

An introduction to a new paradigm in social, technological, and scientific discourse, this book presents an overview of statistical methods for describing, modeling, and inferring biological networks

This book is primarily written for students and researchers dealing with complex ecological problems. Multivariate statistical methods are described, and advice is given on how best to apply these met

There is substantial interest in the application of different statistical methods to model and understand population genetic data. This book aims to fill the vacant niche in books dealing with the app

Many books on reliability focus on either modeling or statistical analysis and require an extensive background in probability and statistics. Continuing its tradition of excellence as an introductory text for those with limited formal education in the subject, this classroom-tested book introduces the necessary concepts in probability and statistics within the context of their application to reliability. The Third Edition adds brief discussions of the Anderson Darling test, the Cox proportionate hazards model, the Accelerated Failure Time model, and Monte Carlo simulation.Over 80 new end-of-chapter exercises have been added, as well as solutions to all odd-numbered exercises. Moreover, Excel workbooks, available for download, save students from performing numerous tedious calculations and allow them to focus on reliability concepts. Ebeling has created an exceptional text that enables readers to learn how to analyze failure, repair data, and derive appropriate models for reliability an

Multivariate Analysis for the Behavioral Sciences, Second Edition is designed to show how a variety of statistical methods can be used to analyse data collected by psychologists and other behavioral s

This book presents mathematical, programming and statistical tools used in the real world analysis and modeling of financial data. The tools are used to model asset returns, measure risk, and construc

Diabetes is a complex disease and is also one of the most common. It is very difficult to reach an accurate estimate for the global prevalence of diabetes since the standards and methods of data coll

Incorporating real examples and data from published sources, this textbook explains how data is collected to characterize samples and populations, and introduces the statistical models and methods use

The Jackknife and bootstrap are the most popular data-resampling methods used in statistical analysis. This book provides a systematic introduction to the theory of the jackknife, bootstrap and other