Independent Random Sampling Methods
This book systematically addresses the design and analysis of efficient techniques for independent random sampling. Both general-purpose approaches, which can be used to generate samples from arbitrary probability distributions, and tailored techniques, d
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Luca Martino David Luengo Joaquín Míguez
Independent Random Sampling Methods QUANTLETS
Statistics and Computing Series editor Wolfgang Karl Härdle, Humboldt University of Berlin, Berlin, Germany
Statistics and Computing (SC) includes monographs and advanced texts on statistical computing and statistical packages.
More information about this series at http://www.springer.com/series/3022
Luca Martino • David Luengo • Joaquín Míguez
Independent Random Sampling Methods
123
Luca Martino Department of Signal Theory and Communications Carlos III University of Madrid Madrid, Spain
David Luengo Department of Signal Theory and Communications Technical University of Madrid Madrid, Spain
Joaquín Míguez Department of Signal Theory and Communications Carlos III University of Madrid Madrid, Spain
The code can be found on GitHub: https://github.com/BookIndRandSamplingMethods/code. Links to all material are available at http://www.springer.com/. ISSN 1431-8784 ISSN 2197-1706 (electronic) Statistics and Computing ISBN 978-3-319-72633-5 ISBN 978-3-319-72634-2 (eBook) https://doi.org/10.1007/978-3-319-72634-2 Library of Congress Control Number: 2018937648 Mathematics Subject Classification (2010): 65C10, 65C05 © Springer International Publishing AG, part of Springer Nature 2018 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by the registered company Springer International Publishing AG part of Springer Nature. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Contents
1
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 1.1 The Monte Carlo Method: A Brief History. . . . . . .. . . . . . . . . . . . . . . . . . . . 1.2 The Need for Monte Carlo . . . . . . . . . . . . . . . . . . . .
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