Monte Carlo methods are among the most used and useful computational tools available, providing efficient and practical algorithms to solve a wide range of scientific and engineering problems. This book provides a hands-on approach to learning this subject.

Hands-on approach is used via realistic problems demonstrated with examples and numerical simulations in Python Applications covered: optimization, finance, statistical mechanics, birth and death processes, and gambling systems Includes supplementary material: sn.pub/extras

Autorentext

Ronald Shonkwiler is also publishing Mathematical Biology: An Introduction with Maple and Matlab, that will will be available in 2008. He is professor emeritus at Georgia Institute of Technology School of Mathematics. He received his PhD in 1970. His areas of expertise include: stochastic processes, optimization, computer simulation, Monte Carlo numerical methods, mathematical biology, and reproducing Kernel Hilbert spaces. Franklin Mendevil is a professor at Acadia University in Nova Scotia. He received his PhD in 1996 at Georgia Institute of Technology. He has co-authored numerous papers and publications, several of which were with Dr. Shonkwiler.

Inhalt
to Monte Carlo Methods.- Some Probability Distributions and Their Uses.- Markov Chain Monte Carlo.- Optimization by Monte Carlo Methods.- Random Walks.