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.
Following a natural progression that assumes no prior knowledge of programming or probability, the book is organised into four main sections:
* Programming In R starts with how to obtain and install R (for Windows, MacOS, and Unix platforms), then tackles basic calculations and program flow, before progressing to function based programming, data structures, graphics, and object-oriented code
* A Primer on Numerical Mathematics introduces concepts of numerical accuracy and program efficiency in the context of root-finding, integration, and optimization
* A Self-contained Introduction to Probability Theory takes readers as far as the Weak Law of Large Numbers and the Central Limit Theorem, equipping them for point and interval estimation
* Simulation teaches how to generate univariate random variables, do Monte-Carlo integration, and variance reduction techniques
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.
發表於2024-12-22
Introduction to Scientific Programming and Simulation Using R 2024 pdf epub mobi 電子書 下載
任何一種編程語言的學習在開始的時候都是一個痛苦的過程,因此在初始階段選擇任何一本書其實沒有多大差彆。差彆在於你已經瞭解最基本的規則之後,培養自己編程的taste的時候。所以google纔會有自己的r編程規範。 http://google-styleguide.googlecode.com/svn/trunk/google-r-...
評分任何一種編程語言的學習在開始的時候都是一個痛苦的過程,因此在初始階段選擇任何一本書其實沒有多大差彆。差彆在於你已經瞭解最基本的規則之後,培養自己編程的taste的時候。所以google纔會有自己的r編程規範。 http://google-styleguide.googlecode.com/svn/trunk/google-r-...
評分任何一種編程語言的學習在開始的時候都是一個痛苦的過程,因此在初始階段選擇任何一本書其實沒有多大差彆。差彆在於你已經瞭解最基本的規則之後,培養自己編程的taste的時候。所以google纔會有自己的r編程規範。 http://google-styleguide.googlecode.com/svn/trunk/google-r-...
評分任何一種編程語言的學習在開始的時候都是一個痛苦的過程,因此在初始階段選擇任何一本書其實沒有多大差彆。差彆在於你已經瞭解最基本的規則之後,培養自己編程的taste的時候。所以google纔會有自己的r編程規範。 http://google-styleguide.googlecode.com/svn/trunk/google-r-...
評分任何一種編程語言的學習在開始的時候都是一個痛苦的過程,因此在初始階段選擇任何一本書其實沒有多大差彆。差彆在於你已經瞭解最基本的規則之後,培養自己編程的taste的時候。所以google纔會有自己的r編程規範。 http://google-styleguide.googlecode.com/svn/trunk/google-r-...
圖書標籤: R 統計 statistics 編程 統計學 Programming 英文版 編程語言
第一部分是R編程入門;第二部分是數值計算,主要是解方程,求積分和優化;第三部分是概率和統計,主要講概率、隨機變量等概念和參數估計,第四部分是simulation,主要講Monte Carlo積分和方差降低。
評分很不錯啊
評分很不錯啊
評分很不錯啊
評分introductory programming
Introduction to Scientific Programming and Simulation Using R 2024 pdf epub mobi 電子書 下載