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
