Preface Chapter 1: Monte Carlo Methods and Quasi-Monte Carlo Methods Chapter 2: Quasi-Monte Carlo Methods for Numerical Integration Chapter 3: Low-Discrepancy Point Sets and Sequences Chapter 4: Nets and (t,s)-Sequences Chapter 5: Lattice Rules for Numerical Integration Chapter 6: Quasi-Monte Carlo Methods for Optimization Chapter 7: Random Numbers and Pseudorandom Numbers Chapter 8: Nonlinear Congruential Pseudorandom Numbers Chapter 9: Shift-Register Pseudorandom Numbers Chapter 10: Pseudorandom Vector Generation Appendix A: Finite Fields and Linear Recurring Sequences Appendix B: Continued Fractions Bibliography Index.
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Description
'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