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Monte Carlo Methods: Monographs on Statistics and Applied Probability

Autor J. Hammersley
en Limba Engleză Paperback – 2 oct 2011
This monograph surveys the present state of Monte Carlo methods. we have dallied with certain topics that have interested us Although personally, we hope that our coverage of the subject is reasonably complete; at least we believe that this book and the references in it come near to exhausting the present range of the subject. On the other hand, there are many loose ends; for example we mention various ideas for variance reduction that have never been seriously appli(:d in practice. This is inevitable, and typical of a subject that has remained in its infancy for twenty years or more. We are convinced Qf:ver­ theless that Monte Carlo methods will one day reach an impressive maturity. The main theoretical content of this book is in Chapter 5; some readers may like to begin with this chapter, referring back to Chapters 2 and 3 when necessary. Chapters 7 to 12 deal with applications of the Monte Carlo method in various fields, and can be read in any order. For the sake of completeness, we cast a very brief glance in Chapter 4 at the direct simulation used in industrial and operational research, where the very simplest Monte Carlo techniques are usually sufficient. We assume that the reader has what might roughly be described as a 'graduate' knowledge of mathematics. The actual mathematical techniques are, with few exceptions, quite elementary, but we have freely used vectors, matrices, and similar mathematical language for the sake of conciseness.
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Specificații

ISBN-13: 9789400958210
ISBN-10: 9400958218
Pagini: 188
Ilustrații: VIII, 178 p.
Dimensiuni: 129 x 198 x 10 mm
Greutate: 0.19 kg
Ediția:Softcover reprint of the original 1st ed. 1964
Editura: SPRINGER NETHERLANDS
Colecția Springer
Seria Monographs on Statistics and Applied Probability

Locul publicării:Dordrecht, Netherlands

Public țintă

Research

Cuprins

1 The general nature of Monte Carlo methods.- 2 Short resumé of statistical terms.- 3 Random, pseudorandom, and quasirandom numbers.- 4 Direct simulation.- 5 General principles of the Monte Carlo method.- 6 Conditional Monte Carlo.- 7 Solution of linear operator equations.- 8 Radiation shielding and reactor criticality.- 9 Problems in statistical mechanics.- 10 Long polymer molecules.- 11 Percolation processes.- 12 Multivariable problems.- References.