Editore: World Scientific Publishing Comp, 1993
ISBN 10: 9810213530 ISBN 13: 9789810213534
Lingua: Inglese
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Editore: World Scientific Publishing Co Pte Ltd, 1994
ISBN 10: 9810213530 ISBN 13: 9789810213534
Lingua: Inglese
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Aggiungi al carrellogebundene Ausgabe. Condizione: Gut. 223 Seiten Das hier angebotene Buch stammt aus einer teilaufgelösten Bibliothek und kann die entsprechenden Kennzeichnungen aufweisen (Rückenschild, Instituts-Stempel.); der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 455.
Editore: World Scientific Publishing Company, 1993
ISBN 10: 9810213530 ISBN 13: 9789810213534
Lingua: Inglese
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Editore: World Scientific Pub Co Inc, 1994
ISBN 10: 9810213530 ISBN 13: 9789810213534
Lingua: Inglese
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Editore: World Scientific Publishing Company, 1993
ISBN 10: 9810213530 ISBN 13: 9789810213534
Lingua: Inglese
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Editore: World Scientific Publishing Company, 1993
ISBN 10: 9810213530 ISBN 13: 9789810213534
Lingua: Inglese
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Editore: World Scientific Publishing Company, 1993
ISBN 10: 9810213530 ISBN 13: 9789810213534
Lingua: Inglese
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Editore: World Scientific Pub Co Inc, 1994
ISBN 10: 9810213530 ISBN 13: 9789810213534
Lingua: Inglese
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Editore: World Scientific Publishing Company, 1993
ISBN 10: 9810213530 ISBN 13: 9789810213534
Lingua: Inglese
Da: GreatBookPrices, Columbia, MD, U.S.A.
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Editore: WORLD SCIENTIFIC PUB CO INC, 1993
ISBN 10: 9810213530 ISBN 13: 9789810213534
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Editore: World Scientific Publishing Company Dez 1993, 1993
ISBN 10: 9810213530 ISBN 13: 9789810213534
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
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Aggiungi al carrelloBuch. Condizione: Neu. Neuware - This volume is the first in the new series Nonlinear Time Series and Chaos. The general aim of the series is to provide a bridge between the two communities by inviting prominent researchers in their respective fields to give a systematic account of their chosen topics, starting at the beginning and ending with the latest state. It is hoped that researchers in both communities will find the topics relevant and thought provoking. In this volume, the first chapter, written by Professor Colleen Cutler, is a comprehensive account of the theory and estimation of fractal dimension, a topic of central importance in dynamical systems, which has recently attracted the attention of the statisticians. As it is natural to study a stochastic dynamical system within the framework of Markov chains, it is therefore relevant to study their limiting behaviour. The second chapter, written by Professor Kung-Sik Chan, reviews some limit theorems of Markov chains and illustrates their relevance to chaos. The next three chapters are concerned with specific models. Briefly, Chapter Three by Professor Peter Lewis and Dr Bonnie Ray and Chapter Four by Professor Peter Brockwell generalise the class of self-exciting threshold autoregressive models in different directions. In Chapter Three, the new and powerful methodology of multivariate adaptive regression splines (MARS) is adapted to time series data. Its versatility is illustrated by reference to the very interesting and complex sea surface temperature data. Chapter Four exploits the greater tractability of continuous-time Markov approach to discrete-time data. The approach is particularly relevant to irregularly sampled data. The concluding chapter, by Professor Pham Dinh Tuan, is likely to be the most definitive account of bilinear models in discrete time to date.