Highly recommended, the best-selling first edition of Introduction to Scientific Programming and Simulation Using R was lauded as an excellent, easy-to-read introduction with extensive examples and exercises. This second edition continues to introduce scientific programming and stochastic modelling in a clear, practical, and thorough way. Readers learn programming by experimenting with the provided R code and data.
The book's four parts teach:
Core knowledge of R and programming concepts
How to think about mathematics from a numerical point of view, including the application of these concepts to root finding, numerical integration, and optimisation
Essentials of probability, random variables, and expectation required to understand simulation
Stochastic modelling and simulation, including random number generation and Monte Carlo integration
In a new chapter on systems of ordinary differential equations (ODEs), the authors cover the Euler, midpoint, and fourth-order Runge-Kutta (RK4) schemes for solving systems of first-order ODEs. They compare the numerical efficiency of the different schemes experimentally and show how to improve the RK4 scheme by using an adaptive step size.
Another new chapter focuses on both discrete- and continuous-time Markov chains. It describes transition and rate matrices, classification of states, limiting behaviour, Kolmogorov forward and backward equations, finite absorbing chains, and expected hitting times. It also presents methods for simulating discrete- and continuous-time chains as well as techniques for defining the state space, including lumping states and supplementary variables.
Building readers' statistical intuition, Introduction to Scientific Programming and Simulation Using R, Second Edition shows how to turn algorithms into code. It is designed for those who want to make tools, not just use them. The code and data are available for download from CRAN.
Описание: Mathematical elegance is a constant theme in this treatment of linear programming and matrix games. This thorough introduction to linear programming and game theory will impart a deep understanding of the material and also increase the student`s mathematical maturity.
Автор: V. G. Kulkarni Название: Introduction to Modeling and Analysis of Stochastic Systems ISBN: 1461427355 ISBN-13(EAN): 9781461427353 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a self-contained review of all the relevant topics in probability theory. A software package called MAXIM, which runs on MATLAB, is made available for downloading. Vidyadhar G. Kulkarni is Professor of Operations Research at the University of North Carolina at Chapel Hill.
Автор: Gerd Infanger Название: Stochastic Programming ISBN: 1461427622 ISBN-13(EAN): 9781461427629 Издательство: Springer Рейтинг: Цена: 32004.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Management Science published in 2005 a special volume featuring the "Ten most Influential Papers of the first 50 Years of Management Science." George Dantzig`s original 1955 stochastic programming paper, "Linear Programming under Uncertainty," was featured among these ten.
Автор: Bober Название: Introduction To Matlab Programming ISBN: 1138032379 ISBN-13(EAN): 9781138032378 Издательство: Taylor&Francis Рейтинг: Цена: 22202.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: All disciplines of science and engineering use numerical methods for complex problem analysis, due to the highly mathematical nature of the field.
Автор: Jagdeep Kaur; Amit Kumar Название: An Introduction to Fuzzy Linear Programming Problems ISBN: 3319312731 ISBN-13(EAN): 9783319312736 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The main focus is on showing current methods for finding the fuzzy optimal solution of fully fuzzy linear programming problems in which all the parameters and decision variables are represented by non-negative fuzzy numbers.
Описание: MATLAB is a programme which lends itself to the implementation of most numerical algorithms. This text, which uses MATLAB, gives an overview of structured programming and numerical methods and covers numerical methods for solving a range of problems, from integration to the numerical solution of differential equations.
Автор: Richard Serfozo Название: Introduction to Stochastic Networks ISBN: 1461271606 ISBN-13(EAN): 9781461271604 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Beginning with Jackson networks and ending with spatial queuing systems, this book describes several basic stochastic network processes, with the focus on network processes that have tractable expressions for the equilibrium probability distribution of the numbers of units at the stations.
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