Applied Nonparametric Statistics in Reliability
Nonparametric statistics has probably become the leading methodology for researchers performing data analysis. It is nevertheless true that, whereas these methods have already proved highly effective in other applied areas of knowledge such as biostatisti
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M. Luz Gámiz K. B. Kulasekera Nikolaos Limnios Bo Henry Lindqvist •
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Applied Nonparametric Statistics in Reliability
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Assoc. Prof. M. Luz Gámiz Depto. Estadistica e Investigacion Operativa, Facultad Ciencias Universidad Granada Campus Univ. Fuentenueva 18071 Granada Spain e-mail: [email protected]
Prof. Nikolaos Limnios Centre de Recherches de Royallieu, Laboratoire de Mathématiques Appliquées Université de Technologie de Compiègne BP 20529 60205 Compiègne France e-mail: [email protected]
Prof. K. B. Kulasekera Department of Mathematical Sciences Clemson University Clemson, SC 29634-1907 USA e-mail: [email protected]
Prof. Bo Henry Lindqvist Department of Mathematical Sciences Norwegian University of Science and Technology 7491 Trondheim Norway e-mail: [email protected]
ISSN 1614-7839 ISBN 978-0-85729-117-2
e-ISBN 978-0-85729-118-9
DOI 10.1007/978-0-85729-118-9 Springer London Dordrecht Heidelberg New York British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Springer-Verlag London Limited 2011 Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms of licenses issued by the Copyright Licensing Agency. Enquiries concerning reproduction outside those terms should be sent to the publishers. The use of registered names, trademarks, etc., in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant laws and regulations and therefore free for general use. The publisher makes no representation, express or implied, with regard to the accuracy of the information contained in this book and cannot accept any legal responsibility or liability for any errors or omissions that may be made. Cover design: eStudio Calamar, Berlin/Figueres Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
This book concerns the use of nonparametric statistical tools for the inferences of the performance characteristics of reliability dynamic systems operating in a certain physical environment that determines their behaviour through time. Although many statistical methods rely on assumptions about the structure of the data to be analysed, there are many practical situations where these assumptions are not satisfied. In such cases, it may not be appropriate to use traditional parametric methods of analysis. In fact, very often a free-model method, and therefore, a data driven focus to the problem, is the only option. The term nonparametric does not mean that there is a complete lack of parameters; rather it implies that the number and the nature of the parameters are not fixe
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