Introduction to Stochastic Programming

International edition of Introduction to Management Science: A Modeling and Case Studies Approach with Spreadsheets 7th Edition. Hillier is especially known for his classic, award-winning text, Introduction to Operations Research, co-authored with the late Gerald J. Lieberman, which has been translated into well over a dozen languages and is currently in its 8th edition. The 6th edition won honorable mention for the 1995 Lanchester Prize (best English-language publication of any kind in the field) and Dr. Hillier also was awarded the 2004 INFORMS Expository Writing Award for the 8th edition. His other books include The Evaluation of Risky Interrelated Investments, Queueing Tables and Graphs, Introduction to Stochastic Models in Operations Research, and Introduction to Mathematical Programming. He received his BS in industrial engineering and doctorate specializing in operations research and management science from Stanford University. The winner of many awards in high school and colleg

This third edition of Braun and Murdoch's bestselling textbook now includes discussion of the use and design principles of the tidyverse packages in R, including expanded coverage of ggplot2, and R Markdown. The expanded simulation chapter introduces the Box–Muller and Metropolis–Hastings algorithms. New examples and exercises have been added throughout. This is the only introduction you'll need to start programming in R, the computing standard for analyzing data. This book comes with real R code that teaches the standards of the language. Unlike other introductory books on the R system, this book emphasizes portable programming skills that apply to most computing languages and techniques used to develop more complex projects. Solutions, datasets, and any errata are available from www.statprogr.science. Worked examples - from real applications - hundreds of exercises, and downloadable code, datasets, and solutions make a complete package for anyone working in or learning practical data

Understand functional programming concepts and the functional nature of the JavaScript language. Starting with an introduction to functional programming concepts, you will learn the key differences be

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This book focuses on maximum principle and verification theorem for incomplete information forward-backward stochastic differential equations (FBSDEs) and their applications in linear-quadratic optima

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This book is based on the lecture notes of the author delivered to the students at the Institute of Science, Banaras Hindu University, India. It covers simplex, revised simplex, two-phase method, dua

If you're interested in data visualization but new to programming or web development, Interactive Data Visualization for the Web gives you what you need to get started creating and publishing your own

Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.

Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.

Get started programming your own fun electronics projects—no experience required!This hands-on guide offers a clear introduction to programming the Intel Galileo using Arduino Software. The book expla

This is the only introduction you'll need to start programming in R, the open-source language that is free to download, and lets you adapt the source code for your own requirements. Co-written by one

This book introduces and studies a number of stochastic models of subsistence, communication, social evolution and political transition that will allow the reader to grasp the role of uncertainty as a

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The first volume of the series is both a simple introduction to the JetBrains MPS language workbench and a complete reference manual. This book explains the MPS programming paradigm and gradually intr

This book is intended to help researchers overcome the entrance barrier to Proper Generalized Decomposition (PGD), by providing a valuable tool to begin the programming task. Detailed Matlab Codes are

Introduction to Computation and Modeling for Differential Equations, Second Edition provides a unified and integrated view of numerical analysis, mathematical modeling in applications, and programming

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Perkovic's Introduction to Programming Using Python: An Application Development Focus, 2e is more than just an introduction to programming. It is an inclusive introduction to Computer Science that tak

Learning Scala is an introduction and a guide to getting started with functional programming (FP) development. Written for programmers who are already familiar with object-oriented (OO) development, t

Lyons’ rough path analysis has provided new insights in the analysis of stochastic differential equations and stochastic partial differential equations, such as the KPZ equation. This textbook present

This concise introduction to the essential concepts in contemporary programming languages features a host of illustrative examples. It explains modern imperative, functional, and logic-based languages

The popular, step-by-step introduction to programming financial engineering applications using C++—now updated with C++ 11 design patternsThe updated and expanded second edition of Daniel Duff

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This book is intended as a text for a two-quarter or two-semester post-calculus introduction to probability and mathematical statistics for undergraduate students in their junior or senior year, and a

?There are several techniques to study noncooperative dynamic games, such as dynamic programming and the maximum principle (also called the Lagrange method). It turns out, however, that one way to cha

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Explores computer-intensive probability and statistics for ecosystem management decision makingSimulation is an accessible way to explain probability and stochastic model behavior to beginners. This b

In its revised and extended second edition, this book covers the basics of bioinformatics/information technology: programming with Bash, Sed and AWK, and the respective terminology. Case studies, exer