Download or read book Probability Models for Economic Decisions written by Roger B. Myerson and published by Duxbury Press. This book was released on 2005 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to use probability in complex realistic situations with PROBABILITY MODELS FOR ECONOMIC DECISIONS. This introduction to the use of probability models for analyzing risks and economic decisions uses Microsoft Excel spreadsheets for the analytic work. As a result of the emphasis on spreadsheet modeling, you'll also develop sophisticated spreadsheet skills.
Download or read book Probability Models for Economic Decisions second edition written by Roger B. Myerson and published by MIT Press. This book was released on 2019-12-17 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the use of probability models for analyzing risk and economic decisions, using spreadsheets to represent and simulate uncertainty. This textbook offers an introduction to the use of probability models for analyzing risks and economic decisions. It takes a learn-by-doing approach, teaching the student to use spreadsheets to represent and simulate uncertainty and to analyze the effect of such uncertainty on an economic decision. Students in applied business and economics can more easily grasp difficult analytical methods with Excel spreadsheets. The book covers the basic ideas of probability, how to simulate random variables, and how to compute conditional probabilities via Monte Carlo simulation. The first four chapters use a large collection of probability distributions to simulate a range of problems involving worker efficiency, market entry, oil exploration, repeated investment, and subjective belief elicitation. The book then covers correlation and multivariate normal random variables; conditional expectation; optimization of decision variables, with discussions of the strategic value of information, decision trees, game theory, and adverse selection; risk sharing and finance; dynamic models of growth; dynamic models of arrivals; and model risk. New material in this second edition includes two new chapters on additional dynamic models and model risk; new sections in every chapter; many new end-of-chapter exercises; and coverage of such topics as simulation model workflow, models of probabilistic electoral forecasting, and real options. The book comes equipped with Simtools, an open-source, free software used througout the book, which allows students to conduct Monte Carlo simulations seamlessly in Excel.
Download or read book Probability Models for Economic Decisions second edition written by Roger B. Myerson and published by MIT Press. This book was released on 2019-12-17 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the use of probability models for analyzing risk and economic decisions, using spreadsheets to represent and simulate uncertainty. This textbook offers an introduction to the use of probability models for analyzing risks and economic decisions. It takes a learn-by-doing approach, teaching the student to use spreadsheets to represent and simulate uncertainty and to analyze the effect of such uncertainty on an economic decision. Students in applied business and economics can more easily grasp difficult analytical methods with Excel spreadsheets. The book covers the basic ideas of probability, how to simulate random variables, and how to compute conditional probabilities via Monte Carlo simulation. The first four chapters use a large collection of probability distributions to simulate a range of problems involving worker efficiency, market entry, oil exploration, repeated investment, and subjective belief elicitation. The book then covers correlation and multivariate normal random variables; conditional expectation; optimization of decision variables, with discussions of the strategic value of information, decision trees, game theory, and adverse selection; risk sharing and finance; dynamic models of growth; dynamic models of arrivals; and model risk. New material in this second edition includes two new chapters on additional dynamic models and model risk; new sections in every chapter; many new end-of-chapter exercises; and coverage of such topics as simulation model workflow, models of probabilistic electoral forecasting, and real options. The book comes equipped with Simtools, an open-source, free software used througout the book, which allows students to conduct Monte Carlo simulations seamlessly in Excel.
Download or read book Statistics Probability for Business and Economic Decisions written by Milad A. Tawadros and published by . This book was released on 1973 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Probability Models and Decisions written by M. P. Wiper and published by . This book was released on 1992-01-01 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Handbook of Probabilistic Models written by Pijush Samui and published by Butterworth-Heinemann. This book was released on 2019-10-05 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Probabilistic Models carefully examines the application of advanced probabilistic models in conventional engineering fields. In this comprehensive handbook, practitioners, researchers and scientists will find detailed explanations of technical concepts, applications of the proposed methods, and the respective scientific approaches needed to solve the problem. This book provides an interdisciplinary approach that creates advanced probabilistic models for engineering fields, ranging from conventional fields of mechanical engineering and civil engineering, to electronics, electrical, earth sciences, climate, agriculture, water resource, mathematical sciences and computer sciences. Specific topics covered include minimax probability machine regression, stochastic finite element method, relevance vector machine, logistic regression, Monte Carlo simulations, random matrix, Gaussian process regression, Kalman filter, stochastic optimization, maximum likelihood, Bayesian inference, Bayesian update, kriging, copula-statistical models, and more. Explains the application of advanced probabilistic models encompassing multidisciplinary research Applies probabilistic modeling to emerging areas in engineering Provides an interdisciplinary approach to probabilistic models and their applications, thus solving a wide range of practical problems
Download or read book Risk Analysis in Theory and Practice written by Jean-Paul Chavas and published by Elsevier. This book was released on 2004-06-04 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of Risk Analysis in Theory and Practice is to present this analytical framework and to illustrate how it can be used in the investigation of economic decisions under risk. In a sense, the economics of risk is a difficult subject: it involves understanding human decisions in the absence of perfect information. How do we make decisions when we do not know some of events affecting us? The complexities of our uncertain world and of how humans obtain and process information make this difficult. In spite of these difficulties, much progress has been made. First, probability theory is the corner stone of risk assessment. This allows us to measure risk in a fashion that can be communicated among decision makers or researchers. Second, risk preferences are now better understood. This provides useful insights into the economic rationality of decision making under uncertainty. Third, over the last decades, good insights have been developed about the value of information. This helps better understand the role of information in human decision making and this book provides a systematic treatment of these issues in the context of both private and public decisions under uncertainty. Balanced treatment of conceptual models and applied analysis Considers both private and public decisions under uncertainty Website presents application exercises in Excel
Download or read book Behavioral Predictive Modeling in Economics written by Songsak Sriboonchitta and published by Springer Nature. This book was released on 2020-08-05 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents both methodological papers on and examples of applying behavioral predictive models to specific economic problems, with a focus on how to take into account people's behavior when making economic predictions. This is an important issue, since traditional economic models assumed that people make wise economic decisions based on a detailed rational analysis of all the relevant aspects. However, in reality – as Nobel Prize-winning research has shown – people have a limited ability to process information and, as a result, their decisions are not always optimal. Discussing the need for prediction-oriented statistical techniques, since many statistical methods currently used in economics focus more on model fitting and do not always lead to good predictions, the book is a valuable resource for researchers and students interested in the latest results and challenges and for practitioners wanting to learn how to use state-of-the-art techniques.
Download or read book Probability Models of Simultaneous Mobility Decisions and Tenure Choice Over Time written by Mingche M. Li and published by . This book was released on 1977 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Probability Models written by John Haigh and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability Models is designed to aid students studying probability as part of an undergraduate course on mathematics or mathematics and statistics. It describes how to set up and analyse models of real-life phenomena that involve elements of chance. Motivation comes from everyday experiences of probability via dice and cards, the idea of fairness in games of chance, and the random ways in which, say, birthdays are shared or particular events arise. Applications include branching processes, random walks, Markov chains, queues, renewal theory, and Brownian motion. No specific knowledge of the subject is assumed, only a familiarity with the notions of calculus, and the summation of series. Where the full story would call for a deeper mathematical background, the difficulties are noted and appropriate references given. The main topics arise naturally, with definitions and theorems supported by fully worked examples and some 200 set exercises, all with solutions.
Download or read book Understanding Probability Models written by Carlos Narciso Bouza Herrera and published by Nova Science Publishers. This book was released on 2020-03 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book intends to highlight how the Theory of Probability supports, not only statistical modeling but how it allows describing different real life phenomena. It gives clues for understanding the philosophic roots of probability and how they are present in different areas of knowledge. The readers may use the book as a source for understanding the philosophical development of probability concepts and of the intents to obtain mathematical models. The chapters deal with the understanding of how probability models are usable for determining: â¢A Probabilistic model of the best flight value for the design on paper of a helicopter â¢How to model the improvement of the behavior of water heating systems and of the reliability of systems â¢Models for determining the probability of non responses in inquiries and to evaluate the missing data. â¢The modeling of various problems related with the behavior of ordering models of use in decision rules and of general properties of Order Statistics. â¢A unified study of the probabilistic aspects of two Metaheuristics: Simulated Annealing and Tabu Search. â¢How to obtain the identification of econometric techniques for dealing efficiently with the study of economic growth models under endogeneity. This book will be of interest for biometricians, statisticians, economists, engineers dealing with control and reliability, as well for informaticians.
Download or read book Uncertain Decisions written by Luigi Luini and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertain Decisions: Bridging Theory and Experiments presents advanced directions of thinking on decision theory - in particular the more recent contributions on non-expected utility theory, fuzzy decision theory and case-based theory. This work also provides theoretical insights on measures of risk aversion and on new problems for general equilibrium analysis. It analyzes how the thinking that underlies the theories described above spills over into real decisions, and how the thinking that underlies these real decisions can explain the discrepancies between theoretical approaches and actual behavior. This work elaborates on how the most recent laboratory experiments have become an important source both for evaluating the leading theory of choice and decision, and for contributing to the formation of new models regarding the subject.
Download or read book Probability Models And Applications Revised Second Edition written by Ingram Olkin and published by World Scientific. This book was released on 2019-09-03 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by renowned experts in the field, this reissue of a textbook has as its unifying theme the role that probability models have had, and continue to have, in scientific and practical applications. It includes many examples, with actual data, of real-world use of probability models, while expositing the mathematical theory of probability at an introductory calculus-based level. Detailed descriptions of the properties and applications of probability models that have successfully modeled real phenomena are given, as well as an explanation of methods for testing goodness of fit of these models. Readers will receive a firm foundation in techniques for deriving distributions of various summaries of data that will prepare them for subsequent studies of statistics, as well as a solid grounding in concepts such as that of conditional probability that will prepare them for more advanced courses in stochastic processes.
Download or read book Project Economics and Decision Analysis Probabilistic models written by M. A. Mian and published by Pennwell Corporation. This book was released on 2002 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive two-volume set provides all the necessary concepts of capital investment evaluation, capital budgeting, and decision analysis. Mian takes the reader step-by-step through the decision making process, providing comprehensive coverage of all decision analysis tools currently available while outlining how investment decisions are made under different stages of risk. Further, he focuses on practical application, using a straightfoward approach with solved 'real-life' examples and solutions, end-of-chapter problems, and illustrations throughout the book.
Download or read book Probability Models in Operations Research written by C. Richard Cassady and published by CRC Press. This book was released on 2008-08-05 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industrial engineering has expanded from its origins in manufacturing to transportation, health care, logistics, services, and more. A common denominator among all these industries, and one of the biggest challenges facing decision-makers, is the unpredictability of systems. Probability Models in Operations Research provides a comprehensive
Download or read book Information and Efficiency in Economic Decision written by Jati Sengupta and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use of information is basic to economic theory in two ways. As a basis for optimization, it is central to all normative hypotheses used in eco nomics, but in decision-making situations it has stochastic and evolution ary aspects that are more dynamic and hence more fundamental. This book provides an illustrative survey of the use of information in econom ics and other decision sciences. Since this area is one of the most active fields of research in modern times, it is not possible to be definitive on all aspects of the issues involved. However questions that appear to be most important in this author's view are emphasized in many cases, without drawing any definite conclusions. It is hoped that these questions would provoke new interest for those beginning researchers in the field who are currently most active. Various classifications of information structures and their relevance for optimal decision-making in a stochastic environment are analyzed in some detail. Specifically the following areas are illustrated in its analytic aspects: 1. Stochastic optimization in linear economic models, 2. Stochastic models in dynamic economics with problems of time-inc- sistency, causality and estimation, 3. Optimal output-inventory decisions in stochastic markets, 4. Minimax policies in portfolio theory, 5. Methods of stochastic control and differential games, and 6. Adaptive information structures in decision models in economics and the theory of economic policy.
Download or read book Probability Models and Applications written by Ingram Olkin and published by . This book was released on 1975 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt:
