Apart from a thorough exploration of all the important concepts, this volume includes over 75 algorithms, ready for putting into practice. The book also contains numerous hands-on implementations of selected algorithms to demonstrate applications in realistic settings. Readers are assumed to have a sound understanding of calculus, introductory matrix analysis, and intermediate statistics, but otherwise the book is self-contained. Suitable for graduates and undergraduates in mathematics and engineering, in particular operations research, statistics, and computer science.

Inhalt

Preface Selected Notation 1 Introduction 2 Estimating Volume and Count 3 Generating Samples 4 Increasing Efficiency 5 Random Tours 6 Designing and Analyzing Sample Paths 7 Generating Pseudorandom Numbers Author Index Subject Index