Introduction to Time Series and Forecasting und über 1 Million weitere Bücher verfügbar für Amazon Kindle . Erfahren Sie mehr

Gebraucht kaufen
Gebraucht - Gut Informationen anzeigen
Preis: EUR 22,80

oder
Loggen Sie sich ein, um 1-Click® einzuschalten.
 
   
Möchten Sie verkaufen? Hier verkaufen
Introduction to Time Series and Forecasting (Springer Texts in Statistics)
 
 
Beginnen Sie mit dem Lesen von Introduction to Time Series and Forecasting auf Ihrem Kindle in weniger als einer Minute.

Sie haben keinen Kindle? Hier kaufen oder eine gratis Kindle Lese-App herunterladen.

Introduction to Time Series and Forecasting (Springer Texts in Statistics) [Englisch] [Gebundene Ausgabe]

Peter J. Brockwell , Richard A. Davis


Erhältlich bei diesen Anbietern.


Weitere Ausgaben

Amazon-Preis Neu ab Gebraucht ab
Kindle Edition EUR 64,08  
Gebundene Ausgabe EUR 91,50  
Gebundene Ausgabe, 1. Januar 1999 --  
Dieses Buch gibt es in einer neuen Auflage:
Introduction to Time Series and Forecasting (Springer Texts in Statistics) Introduction to Time Series and Forecasting (Springer Texts in Statistics)
EUR 91,50
Auf Lager.

Kunden, die diesen Artikel angesehen haben, haben auch angesehen


Produktinformation


Mehr über die Autoren

Entdecken Sie Bücher, lesen Sie über Autoren und mehr

Produktbeschreibungen

Pressestimmen

From the reviews of the second edition: "I like this book very much: as one who teaches an undergraduate course of time series, it covers everything that I require and more. I would have no hesitation in recommending it to my students." The Statistician "This is the second edition of a popular time series course text … . The accompanying computer package is the book’s most appealing feature. It allows one to integrate theoretical discourse and methodologic practice with considerable ease. … In my opinion, this book is the best textbook choice for a course at the advanced undergraduate and master’s level in modern time-series analysis in time and frequency domains. Those who are teaching from other texts are unnecessarily complicating their lives." (Robert Lund, Journal of the American Statistical Association, Vol. 98 (463), 2003) "This is … update to an introductory time series book that first appeared in 1996. … The book is not expensive. … If you need a good basic time series reference, this book would certainly be a good choice." (Technometrics, Vol. 45 (1), 2003) "The book gives an introduction into time series analysis. … The book is highly recommendable. It provides an excellent introduction into time series analysis. … it can be used as a textbook for students of various disciplines. Moreover, it is suitable as a reference book for practitioners. The great number of examples coming from economics, engineering, natural and social sciences contribute to a better understanding of the methods. For handling the software, very little familiarity with computing is required." (Wolfgang Schmid, Zentralblatt MATH, Vol. 994, 2002)

Kurzbeschreibung

Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introducitons are also given to cointegration and to non-linear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.

Welche anderen Artikel kaufen Kunden, nachdem sie diesen Artikel angesehen haben?


In diesem Buch (Mehr dazu)
Nach einer anderen Ausgabe dieses Buches suchen.
Mehr entdecken
Wortanzeiger
Ausgewählte Seiten ansehen
Buchdeckel | Copyright | Inhaltsverzeichnis | Auszug | Stichwortverzeichnis
Hier reinlesen und suchen:

Tags

 (Was ist das?)
Bei einem Tag handelt es sich um ein Schlagwort, das zum Produkt passt.
Tags erleichtern allen Kunden die Suche und die Sortierung ihrer Lieblingsprodukte.
 

Kundenrezensionen

Es gibt noch keine Kundenrezensionen auf Amazon.de
5 Sterne
4 Sterne
3 Sterne
2 Sterne
1 Sterne
Die hilfreichsten Kundenrezensionen auf Amazon.com (beta)
Amazon.com:  15 Rezensionen
38 von 41 Kunden fanden die folgende Rezension hilfreich
Excellent introduction on time series analysis 1. Februar 2001
Von Steve Uhlig - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe
Very good introductory book to ARMA models. Full of real-life examples that provide some intuitive insight about the issues that may arise when modelling time series and forecasting. Requires some initial knowledge in statistics and algebra but if you're involved in time series modelling, it should be your first book.
30 von 32 Kunden fanden die folgende Rezension hilfreich
good modern cover of both time and frequency domains 23. Januar 2008
Von Michael R. Chernick - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe
In contrast to their graduate text "Time Series: Theory and Methods" this book is more elementary and introductory and is pitched at the advanced undergraduate level requiring only calculus, elementary statistics and matrix algebra. It gives very good coverage to a wide variety of time series models and includes some nonstationary models. In this second edition the chapter on nonstationary models includes the latest coverage of ARCH and GARCH models presented in a way that I found very accessible.
Computations are done with ITSM and in this edition the ITSM 2000 version 7.0 edition is included on a CD so that students can reproduce the authors' calculations and run analyses of their own.

Another nice feature of the text that distinguishes it from other texts at this level is the introduction of multivariate time series, coverage of state space models, chaos and cointegration. Ideas are illustrated with examples. Important theory is discussed but is kept brief and theorems and proofs are not given to the extent of their other more theoretical text.
10 von 10 Kunden fanden die folgende Rezension hilfreich
Carelessly put together and VERY unorganized 17. September 2010
Von Young - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe|Von Amazon bestätigter Kauf
First off, my background is as follows: I have taken master's level courses in probability, statistical inference, linear regression, linear algebra, and differential equations from a very reputable university, and received high marks in all classes. Also, I've scored 800 on the Quantitative section of the GRE.

So you would think that a person like myself would find this book to be challenging yet rewarding and manageable. After spending 2 weeks trying to decipher the text, and going over 3 chapters, I've lost all hope in the book. When I read this textbook, it feels as though I am trying to understand the Authors' stream of consciousness.

As a student of math, I am quite used to spending countless hours deciphering the theorems and propositions of many mathematicians. But with this book, I also have the added burden of having to dicipher the Authors' thought process. To be clear, the material in the text book is very good, but the presentation of the material is that of a "rambler." At this point I have given up on the book as a source of my learning, and have purchased another text book to use as my reference.

I agree with the many other reviewers who stated that the book is unorganized and written poorly. It seems as though they spent MINIMAL time on producing this book just to meet a deadline. After the first few chapters, it REALLY gets annoying and makes you want to chastise the Authors for being so irresponsible. They may be geniuses in their field, but they have no right to teach the material with these kinds of products.

*UPDATE* 11DEC2010
I've more or less gone through the entire book(only by necessity since the homework questions were from the text). My opinion of this textbook still stands.
As an alternative I recommend "Analysis of Financial Time Series" by Tsay. I've read bits of it, and it seems very well written and progressive. Helped me out a TON in understanding ARCH/GARCH processes.

Kunden diskutieren

Das Forum zu diesem Produkt
Diskussion Antworten Jüngster Beitrag
Noch keine Diskussionen

Fragen stellen, Meinungen austauschen, Einblicke gewinnen
Neue Diskussion starten
Thema:
Erster Beitrag:
Eingabe des Log-ins
 


Aktive Diskussionen in ähnlichen Foren
Kundendiskussionen durchsuchen
Alle Amazon-Diskussionen durchsuchen
   
Ähnliche Foren


Lieblingslisten

Legen Sie Ihre eigene Lieblingsliste an

Ähnliche Artikel finden


Anhand des Sachgebietes nach ähnlichen Produkten suchen:


Ihr Kommentar