Introduction to Scientific Programming and Simulation Using R

Owen Jones, Robert Maillardet, Andrew Robinson

Praise for the First Edition: "Overall, the authors have produced a highly readable text. As prerequisites do not go beyond first-year calculus, the book should appeal to a wide audience; it should also be eminently suitable for self-study. On a somewhat larger scale, it may help to further establish R as a kind of Swiss Army knife for computational science. I strongly recommend it." -C. Kleiber, Universitat Basel, Basel, Switzerland, in Statistical Papers, March 2012 This book is a good resource for someone who wants to learn R and use R for statistical computing and graphics. It will also serve well as a textbook or a reference book for students in a course related to computational statistics. -Hon Keung Tony Ng, Technometrics, May 2011 ... a very coherent and useful account of its chosen subject matter. ... The programming section ... is more comprehensive than Braun & Murdoch (2007), but more accessible than Venables & Ripley (2000). ... The book deserves a place on university library shelves ... One very useful feature of the book is that nearly every chapter has a set of exercises. There are also plenty of well-chosen examples throughout the book that are used to explain the material. I also appreciated the clear and attractive programming style of the R code presented in the book. I found very little in the way of typos or solecisms. ... I can strongly recommend the book for its intended audience. If I ever again have to teach our stochastic modelling course, I will undoubtedly use some of the exercises and examples from Scientific Programming and Simulation Using R. -David Scott, Australian & New Zealand Journal of Statistics, 2011 It is not often that I think that a statistics text is one that most scientifc statisticians should have in their personal libraries. Introduction to Scientific Programming and Simulation Using R is such a text. ... This text provides scientific researchers with a working knowledge of R for both reviewing and for engaging in the statistical evaluation of scientific data. ...It is particularly useful for understanding and developing modeling and simulation software. I highly recommend the text, finding it to be one of the most useful books I have read on the subject. -Journal of Statistical Software, September 2010, Volume 36 The authors have written an excellent introduction to scientific programming with R. Their clear prose, logical structure, well-documented code and realistic examples made the book a pleasure to read. One particularly useful feature is the chapter of cases studies at the end, which not only demonstrates complete analyses but also acts as a pedagogical tool to review and integrate material introduced throughout the book. ... I would strongly recommend this book for readers interested in using R for simulations, particularly for those new to scientific programming or R. It is also very student-friendly and would be suitable either as a course textbook or for self-study. -Significance, September 2009 I think that the techniques of scientific programming presented will soon enable the novice to apply statistical models to real-world problems. The writing style is easy to read and the book is suitable for private study. If you have never read a book on scientific programming and simulation, then I recommend that you start with this one. -International Statistical Review, 2009

• Programming. Numerical Techniques. Probability and Statistics. Simulation. Glossary of R Commands. Programs and Functions Developed in the Text. Index.