Amazon cover image
Image from Amazon.com

Time Series : Modeling, Computation, and Inference.

By: Contributor(s): Series: Chapman and Hall/CRC Texts in Statistical Science SerPublisher: Philadelphia, PA : CRC Press LLC, 2010Copyright date: ©2010Edition: 1st edDescription: 1 online resource (375 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781439882757
Subject(s): Genre/Form: Additional physical formats: Print version:: Time Series : Modeling, Computation, and InferenceDDC classification:
  • 519.5/5
LOC classification:
  • QA280 .P723 2010
Online resources:
Contents:
Front cover -- Contents -- Preface -- Chapter 1: Notation, definitions, and basic inference -- Chapter 2: Traditional time domain models -- Chapter 3: The frequency domain -- Chapter 4: Dynamic linear models -- Chapter 5: State-space TVAR models -- Chapter 6: General state-space models andsequential Monte Carlo methods -- Chapter 7: Mixture models in time series -- Chapter 8: Topics and examples in multipletime series -- Chapter 9: Vector AR and ARMA models -- Chapter 10: Multivariate DLMs and covariance models -- Bibliography -- Author Index -- Subject Index -- Back cover.
Summary: The authors systematically develop a state-of-the-art analysis and modeling of time series. … this book is well organized and well written. The authors present various statistical models for engineers to solve problems in time series analysis. Readers no doubt will learn state-of-the-art techniques from this book.-Hsun-Hsien Chang, Computing Reviews, March 2012My favorite chapters were on dynamic linear models and vector AR and vector ARMA models.-William Seaver, Technometrics, August 2011… a very modern entry to the field of time-series modelling, with a rich reference list of the current literature, including 85 references from 2008 and later. It is well-written and I spotted very few typos. This textbook can undoubtedly work as a reference manual for anyone entering the field or looking for an update. … I am certain there is more than enough material within Time Series to fill an intense one-semester course.-International Statistical Review (2011), 79.
Holdings
Item type Current library Call number Status Date due Barcode Item holds
Ebrary Ebrary Afghanistan Available EBKAF00091784
Ebrary Ebrary Algeria Available
Ebrary Ebrary Cyprus Available
Ebrary Ebrary Egypt Available
Ebrary Ebrary Libya Available
Ebrary Ebrary Morocco Available
Ebrary Ebrary Nepal Available EBKNP00091784
Ebrary Ebrary Sudan Available
Ebrary Ebrary Tunisia Available
Total holds: 0

Front cover -- Contents -- Preface -- Chapter 1: Notation, definitions, and basic inference -- Chapter 2: Traditional time domain models -- Chapter 3: The frequency domain -- Chapter 4: Dynamic linear models -- Chapter 5: State-space TVAR models -- Chapter 6: General state-space models andsequential Monte Carlo methods -- Chapter 7: Mixture models in time series -- Chapter 8: Topics and examples in multipletime series -- Chapter 9: Vector AR and ARMA models -- Chapter 10: Multivariate DLMs and covariance models -- Bibliography -- Author Index -- Subject Index -- Back cover.

The authors systematically develop a state-of-the-art analysis and modeling of time series. … this book is well organized and well written. The authors present various statistical models for engineers to solve problems in time series analysis. Readers no doubt will learn state-of-the-art techniques from this book.-Hsun-Hsien Chang, Computing Reviews, March 2012My favorite chapters were on dynamic linear models and vector AR and vector ARMA models.-William Seaver, Technometrics, August 2011… a very modern entry to the field of time-series modelling, with a rich reference list of the current literature, including 85 references from 2008 and later. It is well-written and I spotted very few typos. This textbook can undoubtedly work as a reference manual for anyone entering the field or looking for an update. … I am certain there is more than enough material within Time Series to fill an intense one-semester course.-International Statistical Review (2011), 79.

Description based on publisher supplied metadata and other sources.

Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2019. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

There are no comments on this title.

to post a comment.