BIBLIO is the largest independent book marketplace in the world, with over 100 million books.

Skip to content

Introduction to Scientific Programming and Simulation Using R (Chapman & Hall/CRC The R Series)

Introduction to Scientific Programming and Simulation Using R (Chapman & Hall/CRC The R Series)

Introduction to Scientific Programming and Simulation Using R (Chapman &
Stock photo: cover may vary

Introduction to Scientific Programming and Simulation Using R (Chapman & Hall/CRC The R Series) Hardback - 2014

by Jones, Owen; Maillardet, Robert; Robinson, Andrew

Add to wish list
  • Used
  • Good
  • Hardback
Used - Good

Description

Chapman and Hall/CRC, 2014-06-12. hardcover. Good. 6x1x9. Textbook, May Have Highlights, Notes and/or Underlining, BOOK ONLY-NO ACCESS CODE, NO CD, Ships with Tracking
Ask the seller a question Add to wish list
A$135.71
A$5.68 Delivery within USA
Standard delivery: 4 to 14 days
More delivery options
Ships from SGS Trading Inc (New Jersey, United States)
Biblio Top Seller
The BIBLIO Guarantee

Details

About SGS Trading Inc New Jersey, United States

Specialising in: Reference Books, Textbook
Biblio member since 2009

Textbook and Reference Books Discounted

Terms of Sale: 30 day return guarantee, with full refund including shipping costs for up to 30 days after delivery if an item arrives misdescribed or damaged.

Browse books from SGS Trading Inc

Reader reviews for Introduction to Scientific Programming and Simulation Using R (Chapman & Hall/CRC The R Series)

Write a review for this book

There are no reviews for this book yet. Be the first to write a review!

Your review will be anonymous unless you login or create an account first.

Overall rating
Remember: You’re rating the book as a work, not the seller or the condition of the specific copy you purchased!

Important Terms and Guidelines

  • Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
  • Reviews must be at least 140 characters in length.
  • Please do not reveal critical plot elements.
  • This is not a help line. Contact customer support if you need help.
Your review must not include:
  • Obscenities, discriminatory language, or other insulting language not suitable for public domain
  • Advertisements, “spam” content, or references to other products, offers or websites.
  • Email addresses, URLs, phone numbers, physical addresses or other contact information.
  • Overly critical comments about other reviews or reviewers
  • Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
  • Availability, price, or alternative ordering/shipping information

From the publisher

Learn How to Program Stochastic Models

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.

About the author

Owen Jones, Robert Maillardet, Andrew Robinson

Please wait a moment while we load the requested page.

tracking-