Statistical Simulation and Computational Methods: Monte Carlo, MCMC, and Stochastic Differential Equations - Softcover

Fourar, Yasmine

 
9786209907302: Statistical Simulation and Computational Methods: Monte Carlo, MCMC, and Stochastic Differential Equations

Inhaltsangabe

This book develops the core numerical methods used in modern statistical computing, with an emphasis on Monte Carlo techniques and their theoretical foundations. Starting from basic probability concepts, the text covers the simulation of random variables, the estimation of integrals via Monte Carlo, and practical variance reduction strategies that improve computational efficiency. It then addresses the challenges of Bayesian inference, introducing Markov chain Monte Carlo algorithms as tools for sampling from complex, high¿dimensional distributions. The treatment extends to stochastic differential equations, where numerical discretisation schemes such as Euler-Maruyama and Milstein are presented for simulating continuous¿time processes. Throughout, the material balances mathematical rigor with algorithmic implementation, supported by examples and step¿by¿step procedures. The book is designed for graduate students and researchers in statistics, data science, finance, and engineering who need a practical yet theoretically sound introduction to computational statistics.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Über die Autorin bzw. den Autor

Yasmine Fourar holds a PhD in mathematics. Her research focuses on numerical methods. This book grew out of her lecture notes for a course on numerical statistics and stochastic modeling.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.