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The application of engineering principles in divergent fields such as management science and communications as well as the advancement of several approaches in theory and computation have led to growing interest in queueing models, creating the need for a comprehensive text. Emphasizing Markovian structures and the techniques that occur in differen
A Cohesive Approach to Regression Models Confidence Intervals in Generalized Regression Models introduces a unified representation-the generalized regression model (GRM)-of various types of regression models. It also uses a likelihood-based approach for performing statistical inference from statistical evidence consisting of data a
Handbook of Empirical Economics and Finance explores the latest developments in the analysis and modeling of economic and financial data. Well-recognized econometric experts discuss the rapidly growing research in economics and finance and offer insight on the future direction of these fields. Focusing on micro models, the first group of chapters describes the statistical issues involved in the analysis of econometric models with cross-sectional data often arising in microeconomics. The book then illustrates time series models that are extensively used in empirical macroeconomics and finance. The last set of chapters explores the types of panel data and spatial models that are becoming increasingly significant in analyzing complex economic behavior and policy evaluations. This handbook brings together both background material and new methodological and applied results that are extremely important to the current and future frontiers in empirical economics and finance. It emphasizes inferential issues that transpire in the analysis of cross-sectional, time series, and panel data-based empirical models in economics, finance, and related disciplines.
Since the emerging discipline of engineering enterprise systems extends traditional systems engineering to develop webs of systems and systems-of-systems, the engineering management and management science communities need new approaches for analyzing and managing risk in engineering enterprise systems. Advanced Risk Analysis in Engineering Enterpri
Reviewing the theory of the general linear model (GLM) using a general framework, Univariate and Multivariate General Linear Models: Theory and Applications with SAS, Second Edition presents analyses of simple and complex models, both univariate and multivariate, that employ data sets from a variety of disciplines, such as the social and behavioral sciences. With revised examples that include options available using SAS 9.0, this expanded edition divides theory from applications within each chapter. Following an overview of the GLM, the book introduces unrestricted GLMs to analyze multiple regression and ANOVA designs as well as restricted GLMs to study ANCOVA designs and repeated measuremen...
Virtually any random process developing chronologically can be viewed as a time series. In economics, closing prices of stocks, the cost of money, the jobless rate, and retail sales are just a few examples of many. Developed from course notes and extensively classroom-tested, Applied Time Series Analysis includes examples across a variety of fields, develops theory, and provides software to address time series problems in a broad spectrum of fields. The authors organize the information in such a format that graduate students in applied science, statistics, and economics can satisfactorily navigate their way through the book while maintaining mathematical rigor. One of the unique features of ...
A Text on the Foundation Processes, Analytical Principles, and Implementation Practices of Engineering Risk Management Drawing from the author's many years of hands-on experience in the field, Analytical Methods for Risk Management: A Systems Engineering Perspectivepresents the foundation processes and analytical practices
The number of innovative applications of randomization tests in various fields and recent developments in experimental design, significance testing, computing facilities, and randomization test algorithms have necessitated a new edition of Randomization Tests. Updated, reorganized, and revised, the text emphasizes the irrelevance and implausibility of the random sampling assumption for the typical experiment in three completely rewritten chapters. It also discusses factorial designs and interactions and combines repeated-measures and randomized block designs in one chapter. The authors focus more attention on the practicality of N-of-1 randomization tests and the availability of user-friendl...
State-of-the-Art Coverage of the Most Widely Used Acceptance Sampling Techniques Cohesively Incorporates Theory and Practice Reflecting the recent resurgence of interest in this field, Acceptance Sampling in Quality Control, Second Edition presents the state of the art in the methodology of sampling and explores its advantages and limitations. The book also looks at how acceptance control can support applications of statistical process control and help in the evaluation of products. New to the Second Edition Coverage of ISO 2859 and 3951 standards and the ASTM version (E2234) of MIL-STD-105E A new section on credit-based sampling plans Greater emphasis on sampling schemes with switching rule...
Through clear, step-by-step mathematical calculations, Applied Statistical Inference with MINITAB enables students to gain a solid understanding of how to apply statistical techniques using a statistical software program. It focuses on the concepts of confidence intervals, hypothesis testing, validating model assumptions, and power analysis.Illustr