Random Number Generation and Quasi-Monte Carlo Methods

• PrefaceChapter 1: Monte Carlo Methods and Quasi-Monte Carlo MethodsChapter 2: Quasi-Monte Carlo Methods for Numerical IntegrationChapter 3: Low-Discrepancy Point Sets and SequencesChapter 4: Nets and (t,s)-SequencesChapter 5: Lattice Rules for Numerical IntegrationChapter 6: Quasi-Monte Carlo Methods for OptimizationChapter 7: Random Numbers and Pseudorandom NumbersChapter 8: Nonlinear Congruential Pseudorandom NumbersChapter 9: Shift-Register Pseudorandom NumbersChapter 10: Pseudorandom Vector GenerationAppendix A: Finite Fields and Linear Recurring SequencesAppendix B: Continued FractionsBibliographyIndex.

'The most important sections of this book deal with the fundamental concepts of nets, (t, s)-sequences, and lattice rules which are of central importance in new advances in quasi-Monte Carlo methods ... It gives an excellent survey on the recent developments in uniform pseudorandom number generation and quasi-Monte Carlo methods. Some of these developments described here have never before presented in a book ...Fundamental concepts and methods were explained in detail using instructive examples (e.g. numerical integration in higher dimensions, optimization ...). Hence, this publication should also be accessible for nonspecialists. For the scientific computing community it is surely a valuable contribution.' U. Lotz, Biometric Journal