Introduction to Scientific Programming and Simulation Using R (Repost)
Introduction to Scientific Programming and Simulation Using R By Owen Jones, Robert Maillardet, Andrew Robinson
2009 | 449 Pages | ISBN: 1420068725 | PDF | 8 MB
2009 | 449 Pages | ISBN: 1420068725 | PDF | 8 MB
Known for its versatility, the free programming language R is widely used for statistical computing and graphics, but is also a fully functional programming language well suited to scientific programming. An Introduction to Scientific Programming and Simulation Using R teaches the skills needed to perform scientific programming while also introducing stochastic modelling. Stochastic modelling in particular, and mathematical modelling in general, are intimately linked to scientific programming because the numerical techniques of scientific programming enable the practical application of mathematical models to real-world problems. In the last section, stochastic modelling is introduced using extensive case studies on epidemics, inventory management, and plant dispersal. A tried and tested pedagogic approach is employed throughout, with numerous examples, exercises, and a suite of practice projects. Unlike most guides to R, this volume is not about the application of statistical techniques, but rather shows how to turn algorithms into code. It is for those who want to make tools, not just use them.