simulation statistical modeling and decision science

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Decision Sciences

Author : Raghu Nandan Sengupta
ISBN : 9781482282566
Genre : Business & Economics
File Size : 35. 74 MB
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This handbook is an endeavour to cover many current, relevant, and essential topics related to decision sciences in a scientific manner. Using this handbook, graduate students, researchers, as well as practitioners from engineering, statistics, sociology, economics, etc. will find a new and refreshing paradigm shift as to how these topics can be put to use beneficially. Starting from the basics to advanced concepts, authors hope to make the readers well aware of the different theoretical and practical ideas, which are the focus of study in decision sciences nowadays. It includes an excellent bibliography/reference/journal list, information about a variety of datasets, illustrated pseudo-codes, and discussion of future trends in research. Covering topics ranging from optimization, networks and games, multi-objective optimization, inventory theory, statistical methods, artificial neural networks, times series analysis, simulation modeling, decision support system, data envelopment analysis, queueing theory, etc., this reference book is an attempt to make this area more meaningful for varied readers. Noteworthy features of this handbook are in-depth coverage of different topics, solved practical examples, unique datasets for a variety of examples in the areas of decision sciences, in-depth analysis of problems through colored charts, 3D diagrams, and discussions about software.

Simulation

Author : Sheldon M. Ross
ISBN : 9780080517223
Genre : Mathematics
File Size : 37. 61 MB
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Ross's Simulation, Fourth Edition introduces aspiring and practicing actuaries, engineers, computer scientists and others to the practical aspects of constructing computerized simulation studies to analyze and interpret real phenomena. Readers learn to apply results of these analyses to problems in a wide variety of fields to obtain effective, accurate solutions and make predictions about future outcomes. This text explains how a computer can be used to generate random numbers, and how to use these random numbers to generate the behavior of a stochastic model over time. It presents the statistics needed to analyze simulated data as well as that needed for validating the simulation model. New to this Edition: -More focus on variance reduction, including control variables and their use in estimating the expected return at blackjack and their relation to regression analysis -A chapter on Markov chain monte carlo methods with many examples -Unique material on the alias method for generating discrete random variables

Regenerative Stochastic Simulation

Author : Gerald S. Shedler
ISBN : 9780080925721
Genre : Mathematics
File Size : 57. 27 MB
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Simulation is a controlled statistical sampling technique that can be used to study complex stochastic systems when analytic and/or numerical techniques do not suffice. The focus of this book is on simulations of discrete-event stochastic systems; namely, simulations in which stochastic state transitions occur only at an increasing sequence of random times. The discussion emphasizes simulations on a finite or countably infinite state space. * Develops probabilistic methods for simulation of discrete-event stochastic systems * Emphasizes stochastic modeling and estimation procedures based on limit theorems for regenerative stochastic processes * Includes engineering applications of discrete-even simulation to computer, communication, manufacturing, and transportation systems * Focuses on simulations with an underlying stochastic process that can specified as a generalized semi-Markov process * Unique approach to simulation, with heavy emphasis on stochastic modeling * Includes engineering applications for computer, communication, manufacturing, and transportation systems

Modeling For All Scales

Author : Howard T. Odum
ISBN : 0080544363
Genre : Science
File Size : 59. 76 MB
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All manner of models are used to describe, simulate, extrapolate, and ultimately understand the function of dynamic systems. These sorts of models are usually based upon a mathematical foundation that can be difficult to manipulate especially for students. Modeling for All Scales uses object-oriented programming to erect and evaluate the efficacy of models of small, intermediate and large scale systems. Such models allow users to employ intuitively based symbols and a systems ecology approach. The authors have been leaders in the systems ecology community and have originated much of the scientific vocabulary of the field. After introducing modeling and its benefits, there is a series of chapters detailing the more particular elements of successful simulation. There follows another series of chapters, each devoted to models of different sorts of systems. Small scale models of growth, competition, and evolution give way, successively, to larger and larger scale models such as international trade and the global geobiosphere. Anyone interested in an easy to use approach to modeling complex systems authored by perhaps the most original systems ecologists of the century will want this book. To further enhance the users ability to apply the lessons of this book, there is included a CD-ROM disc which provides the fundamental tools for modeling at all scales. Key Features * The book makes it possible to teach modeling and simulation without much prior knowledge of mathematics * Reasons for modeling and simulation are discussed * The book makes modeling and simulation fun by keeping focused on simplified overview minimodels that have important principles to science and society * The steps in successive chapters are arranged so that readers can teach themselves modeling, simulation, and the programming necessary to simulate the systems they diagram * The CD-ROM has minimodel programs and versions of QuickBasic and EXTEND to run them

Probability And Statistics Volume Ii

Author : Reinhard Viertl
ISBN : 9781848260535
Genre : Mathematics
File Size : 41. 8 MB
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Probability and Statistics theme is a component of Encyclopedia of Mathematical Sciences in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. The Theme with contributions from distinguished experts in the field, discusses Probability and Statistics. Probability is a standard mathematical concept to describe stochastic uncertainty. Probability and Statistics can be considered as the two sides of a coin. They consist of methods for modeling uncertainty and measuring real phenomena. Today many important political, health, and economic decisions are based on statistics. This theme is structured in five main topics: Probability and Statistics; Probability Theory; Stochastic Processes and Random Fields; Probabilistic Models and Methods; Foundations of Statistics, which are then expanded into multiple subtopics, each as a chapter. These three volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers and NGOs.

Data Analysis And Decision Making

Author : S. Albright
ISBN : 9780538476126
Genre : Business & Economics
File Size : 50. 99 MB
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DATA ANALYSIS AND DECISION MAKING emphasizes data analysis, modeling, and spreadsheet use in statistics and management science. This text became a market leader in its first edition for its clarity of writing and teach-by-example approach, and it continues that tradition in this edition. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Introduction To Business Analytics Using Simulation

Author : Jonathan P. Pinder
ISBN : 9780128104866
Genre : Business & Economics
File Size : 71. 73 MB
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Introduction to Business Analytics Using Simulation employs an innovative strategy to teach business analytics. It uses simulation modeling and analysis as mechanisms to introduce and link predictive and prescriptive modeling. Because managers can't fully assess what will happen in the future, but must still make decisions, the book treats uncertainty as an essential element in decision-making. Its use of simulation gives readers a superior way of analyzing past data, understanding an uncertain future, and optimizing results to select the best decision. With its focus on the uncertainty and variability of business, this comprehensive book provides a better foundation for business analytics than standard introductory business analytics books. Students will gain a better understanding of fundamental statistical concepts that are essential to marketing research, Six-Sigma, financial analysis, and business analytics. Winner of the 2017 Textbook and Academic Authors Association (TAA) Most Promising New Textbook Award. Teaches managers how they can use business analytics to formulate and solve business problems to enhance managerial decision-making Explains the processes needed to develop, report, and analyze business data Describes how to use and apply business analytics software

Optimization Techniques In Statistics

Author : Jagdish S. Rustagi
ISBN : 9781483295718
Genre : Mathematics
File Size : 62. 71 MB
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Statistics help guide us to optimal decisions under uncertainty. A large variety of statistical problems are essentially solutions to optimization problems. The mathematical techniques of optimization are fundamentalto statistical theory and practice. In this book, Jagdish Rustagi provides full-spectrum coverage of these methods, ranging from classical optimization and Lagrange multipliers, to numerical techniques using gradients or direct search, to linear, nonlinear, and dynamic programming using the Kuhn-Tucker conditions or the Pontryagin maximal principle. Variational methods and optimization in function spaces are also discussed, as are stochastic optimization in simulation, including annealing methods. The text features numerous applications, including: Finding maximum likelihood estimates Markov decision processes Programming methods used to optimize monitoring of patients in hospitals Derivation of the Neyman-Pearson lemma The search for optimal designs Simulation of a steel mill Suitable as both a reference and a text, this book will be of interest to advanced undergraduate or beginning graduate students in statistics, operations research, management and engineering sciences, and related fields. Most of the material can be covered in one semester by students with a basic background in probability and statistics. Key Features * Covers optimization from traditional methods to recent developments such as Karmarkars algorithm and simulated annealing * Develops a wide range of statistical techniques in the unified context of optimization * Discusses applications such as optimizing monitoring of patients and simulating steel mill operations * Treats numerical methods and applications Includes exercises and references for each chapter * Covers topics such as linear, nonlinear, and dynamic programming, variational methods, and stochastic optimization

Assessing The Reliability Of Complex Models

Author : Committee on Mathematical Foundations of Verification, Validation, and Uncertainty Quantification
ISBN : 9780309256346
Genre : Mathematics
File Size : 60. 68 MB
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Advances in computing hardware and algorithms have dramatically improved the ability to simulate complex processes computationally. Today's simulation capabilities offer the prospect of addressing questions that in the past could be addressed only by resource-intensive experimentation, if at all. Assessing the Reliability of Complex Models recognizes the ubiquity of uncertainty in computational estimates of reality and the necessity for its quantification. As computational science and engineering have matured, the process of quantifying or bounding uncertainties in a computational estimate of a physical quality of interest has evolved into a small set of interdependent tasks: verification, validation, and uncertainty of quantification (VVUQ). In recognition of the increasing importance of computational simulation and the increasing need to assess uncertainties in computational results, the National Research Council was asked to study the mathematical foundations of VVUQ and to recommend steps that will ultimately lead to improved processes. Assessing the Reliability of Complex Models discusses changes in education of professionals and dissemination of information that should enhance the ability of future VVUQ practitioners to improve and properly apply VVUQ methodologies to difficult problems, enhance the ability of VVUQ customers to understand VVUQ results and use them to make informed decisions, and enhance the ability of all VVUQ stakeholders to communicate with each other. This report is an essential resource for all decision and policy makers in the field, students, stakeholders, UQ experts, and VVUQ educators and practitioners.

The Best Thinking In Business Analytics From The Decision Sciences Institute

Author : Decision Sciences Institute
ISBN : 9780134073057
Genre : Computers
File Size : 67. 74 MB
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Today, business success depends on making great decisions – and making them fast. Leading organizations apply sophisticated business analytics tools and technologies to evaluate vast amounts of data, glean new insights, and increase both the speed and quality of decision making. In The Best Thinking and Practices in Business Analytics from the Decision Sciences Institute , DSI has compiled award-winning and award-nominated contributions from its most recent conferences: papers that illuminate exceptionally high-value applications and research on analytics for decision-making. These papers have appeared in no other DSI collection. Explore them here, and you’ll discover powerful new opportunities for competitive advantage through analytics. For all business, academic, and organizational professionals concerned with the science of more effective decision-making; and for undergraduate students, graduate students, and certification candidates in all related fields.

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