Introducing Monte Carlo Methods with R

• Main Authors: Robert, Christian. (Author), Casella, George. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic
• Language: English
• Published: New York, NY : Springer New York, 2010.
• Series: Use R
• Subjects: Statistics.; Computer science.; Computer simulation.; Computer science > Mathematics.; Distribution (Probability theory).; Mathematical statistics.; Engineering mathematics.; Statistics and Computing/Statistics Programs.; Simulation and Modeling.; Computational Mathematics and Numerical Analysis.; Probability and Statistics in Computer Science.; Appl.Mathematics/Computational Methods of Engineering.; Probability Theory and Stochastic Processes.
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-4419-1576-4

Computational techniques based on simulation have now become an essential part of the statistician's toolbox. It is thus crucial to provide statisticians with a practical understanding of those methods, and there is no better way to develop intuition and skills for simulation than to use simula...

Table of Contents:

• Basic R programming
• Random variable generation
• Monte Carlo integration
• Controling and accelerating convergence
• Monte Carlo Optimization
• Metropolis-Hastings algorithms
• Gibbs samplers
• Convergence Monitoring for MCMC algorithms.