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Applied Modeling Techniques and Data Analysis 2


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       Big Data, Artificial Intelligence and Data Analysis Set

      coordinated by

      Jacques Janssen

      Volume 8

      Applied Modeling Techniques and Data Analysis 2

       Financial, Demographic, Stochastic and Statistical Models and Methods

       Edited by

      Yannis Dimotikalis

      Alex Karagrigoriou

      Christina Parpoula

      Christos H. Skiadas

      First published 2021 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.

      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 and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:

      ISTE Ltd

      27-37 St George’s Road

      London SW19 4EU

      UK

       www.iste.co.uk

      John Wiley & Sons, Inc.

      111 River Street

      Hoboken, NJ 07030

      USA

       www.wiley.com

      © ISTE Ltd 2021

      The rights of Yannis Dimotikalis, Alex Karagrigoriou, Christina Parpoula and Christos H. Skiadas to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.

      Library of Congress Control Number: 2020951002

      British Library Cataloguing-in-Publication Data

      A CIP record for this book is available from the British Library

      ISBN 978-1-78630-674-6

      Preface

      Data analysis as an area of importance has grown exponentially, especially during the past couple of decades. This can be attributed to a rapidly growing technology industry and the wide applicability of computational techniques, in conjunction with new advances in analytic tools. Modeling enables analysts to apply various statistical models to the data they are investigating, to identify relationships between variables, to make predictions about future sets of data, as well as to understand, interpret and visualize the extracted information more strategically. Many new research results have recently been developed and published and many more are developing and in progress at the present time. The topic is also widely presented at many international scientific conferences and workshops. This being the case, the need for the literature that addresses this is self-evident. This book includes the most recent advances on the topic. As a result, on one hand, it unifies in a single volume all new theoretical and methodological issues and, on the other, introduces new directions in the field of applied data analysis and modeling, which are expected to further