This textbook approaches optimization from a multi-aspect, multi-criteria perspective. By using a Multiple Criteria Decision Making (MCDM) approach, it avoids the limits and oversimplifications that can come with optimization models with one criterion. The book is presented in a concise form, addressing how to solve decision problems in sequences of intelligence, modelling, choice and review phases, often iterated, to identify the most preferred decision variant. The approach taken is huma...

Boost Your grades with this illustrated Study Guide. You will use it from an undergraduate school all the way to graduate school and beyond.FEATURES:- Written in concise and clear English - Illustrated with graphs and diagrams - Use your down time to prepare for an exam. - Includes Glossary of probability and statistics TABLE OF CONTENTS:Introduction: History Conceptual overview Statistical methods Specialized disciplines SoftwareProbability: Event Statistical Independence Interpretations ...

CAUSAL INFERENCE IN STATISTICSA PrimerCausality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding arsenal of methods that can...

This book is for anyone who has biomedical data and needs to identify variables that predict an outcome, for two-group outcomes such as tumor/not-tumor, survival/death, or response from treatment. Statistical learning machines are ideally suited to these types of prediction problems, especially if the variables being studied may not meet the assumptions of traditional techniques. Learning machines come from the world of probability and computer science but are not yet widely used in biomed...

Fuzzy Multicriteria Decision-Making: Models, Algorithms and Applications addresses theoretical and practical gaps in considering uncertainty and multicriteria factors encountered in the design, planning, and control of complex systems. Including all prerequisite knowledge and augmenting some parts with a step-by-step explanation of more advanced concepts, the authors provide a systematic and comprehensive presentation of the concepts, design methodology, and detailed algorithms. T...

Quantile regression is gradually emerging as a unified statistical methodology for estimating models of conditional quantile functions. By complementing the exclusive focus of classical least squares regression on the conditional mean, quantile regression offers a systematic strategy for examining how covariates influence the location, scale and shape of the entire response distribution. This monograph is the first comprehensive treatment of the subject, encompassing models that are linear...

Throughout the book, theoretical foundations necessary for understanding Electronic Commerce (EC) are presented, ranging from consumer behavior to the economic theory of competition. Furthermore, this book presents the most current topics relating to EC as described by a diversified team of experts in a variety of fields, including a senior vice president of an e-commerce-related company. The authors provide website resources, numerous exercises, and extensive references to supplement the ...

This book honours the outstanding contributions of Vladimir Vapnik, a rare example of a scientist for whom the following statements hold true simultaneously: his work led to the inception of a new field of research, the theory of statistical learning and empirical inference; he has lived to see the field blossom; and he is still as active as ever. He started analyzing learning algorithms in the 1960s and he invented the first version of the generalized portrait algorithm. He later develope...

Why does the World Need—Excel Data Analysis, Modeling, and Simulation? When spreadsheets ?rst became widely available in the early 1980s, it spawned a revolution in teaching. What previously could only be done with arcane software and large scale computing was now available to the common-man, on a desktop. Also, before spreadsheets, most substantial analytical work was done outside the classroom where the tools were; spreadsheets and personal computers moved the work into the classroom. No...

One of the main aims of management accounting is to provide managers with accurate information in order to provide a good basis for decision-making. There is evidence that the information provided by management accounting systems (MAS) is distorted and the occurrence of biases in accounting information is widely accepted among users of MAS. At the same time, the intensity and the frequency of use of MAS increase, too. Consequently, the quality of the provided information is critical. The f...

Practical Goal Programming is intended to allow academics and practitioners to be able to build effective goal programming models, to detail the current state of the art, and to lay the foundation for its future development and continued application to new and varied fields. Suitable as both a text and reference, its nine chapters first provide a brief history, fundamental definitions, and underlying philosophies, and then detail the goal programming variants and ...

Uncertain computation is a system of computation and reasoning in which the objects of computation are not values of variables but restrictions on values of variables.This compendium includes uncertain computation examples based on interval arithmetic, probabilistic arithmetic, fuzzy arithmetic, Z-number arithmetic, and arithmetic with geometric primitives.The principal problem with the existing decision theories is that they do not have capabilities to deal with such environment. Up to no...