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Time Series Analysis and Its Applications: With R Examples (Springer Text - GOOD
US $56.88
Condition:
Good
A book that has been read but is in good condition. Very minimal damage to the cover including scuff marks, but no holes or tears. The dust jacket for hard covers may not be included. Binding has minimal wear. The majority of pages are undamaged with minimal creasing or tearing, minimal pencil underlining of text, no highlighting of text, no writing in margins. No missing pages. See the seller’s listing for full details and description of any imperfections.
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eBay item number:276409743719
Item specifics
- Condition
- Brand
- Unbranded
- Book Title
- Time Series Analysis and Its Applications: With R Examples (Spri
- MPN
- Does not apply
- ISBN
- 9781461427599
- Subject Area
- Mathematics, Medical
- Publication Name
- Time Series Analysis and Its Applications : with R Examples
- Publisher
- Springer
- Item Length
- 9.3 in
- Subject
- Biostatistics, Probability & Statistics / General, Probability & Statistics / Time Series
- Publication Year
- 2012
- Series
- Springer Texts in Statistics Ser.
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Item Height
- 0.5 in
- Item Weight
- 32.7 Oz
- Item Width
- 6.1 in
- Number of Pages
- Xi, 596 Pages
About this product
Product Identifiers
Publisher
Springer
ISBN-10
1461427592
ISBN-13
9781461427599
eBay Product ID (ePID)
159923468
Product Key Features
Number of Pages
Xi, 596 Pages
Publication Name
Time Series Analysis and Its Applications : with R Examples
Language
English
Publication Year
2012
Subject
Biostatistics, Probability & Statistics / General, Probability & Statistics / Time Series
Type
Textbook
Subject Area
Mathematics, Medical
Series
Springer Texts in Statistics Ser.
Format
Trade Paperback
Dimensions
Item Height
0.5 in
Item Weight
32.7 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Edition Number
3
Intended Audience
Scholarly & Professional
Dewey Edition
22
Reviews
From the reviews of the third edition: "This is the third edition of a textbook first published in 2000. The text is intended as a course text for a time series analysis class at the graduate level. ... the appendix includes everything that is necessary to understand the mathematics of time series analysis. As such, there is no way to describe the whole philosophy of the last half century to time series models better than this book." (Wolfgang Polasek, International Statistical Review, Vol. 81 (2), 2014) "The book is organised in 7 chapters and 4 appendices. ... the book is a valuable resource for students at undergraduate and graduate levels and researchers. The R code for almost all the numerical examples, and the appendices with tutorials containing basic R and R time series commands, are helpful for a better understanding of the theoretical concepts by bringing the theory into a more practical context." (Irina Ioana Mohorianu, zbMATH, Vol. 1276, 2014)
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
519.55
Synopsis
Time Series Analysis and Its Applications presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty. The book is designed to be useful as a text for graduate level students in the physical, biological and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonlinear models, resampling techniques, GARCH models, stochastic volatility, wavelets and Markov chain Monte Carlo integration methods. The third edition includes a new section on testing for unit roots and the material on state-space modeling, ARMAX models, and regression with autocorrelated errors has been expanded. Also new to this edition is the enhanced use of the freeware statistical package R. In particular, R code is now included in the text for nearly all of the numerical examples. Data sets and additional R scripts are now provided in one file that may be downloaded via the World Wide Web. This R supplement is a small compressed file that can be loaded easily into R making all the data sets and scripts available to the user with one simple command. The website for the text includes the code used in each example so that the reader may simply copy-and-paste code directly into R. Appendix R, which is new to this edition, provides a reference for the data sets and our R scripts that are used throughout the text. In addition, Appendix R includes a tutorial on basic R commands as well as an R time series tutorial., Time Series Analysis and Its Applications, presents a comprehensive treatment of both time and frequency domain methods with accompanying theory. Extensive examples illustrate solutions to climate change, monitoring a nuclear test ban treaty, evaluating the volatility of an asset, and more., Time Series Analysis and Its Applications presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty. The book is designed to be useful as a text for graduate level students in the physical, biological and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonlinear models, resampling techniques, GARCH models, stochastic volatility, wavelets and Markov chain Monte Carlo integration methods. The third edition includes a new section on testing for unit roots and the material on state-space modeling, ARMAX models, and regression with autocorrelated errors has been expanded. Also new to this edition is the enhanced use of the freeware statistical package R. In particular, R code is now included in the text for nearly all of the numerical examples. Data sets and additional R scripts are now provided in one file that may be downloaded via the World Wide Web. This R supplement is a small compressed file that can be loaded easily into R making all the data sets and scripts available to the user with one simple command. The website for the text includes the code used in each example so that the reader may simply copy-and-paste code directly into R. Appendix R, which is new to this edition, provides a reference for the data sets and our R scripts that are used throughout the text. In addition, Appendix R includes a tutorial on basic R commands as well as an R time series tutorial.
LC Classification Number
QA276-280QA276-280
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- v***n (228)- Feedback left by buyer.Past 6 monthsVerified purchaseThis is an outstanding seller to deal with. Fair prices that are more than reasonable in this economy. The product is in better condition than described, a true value for my money. Packaged and shipped well shows seller has concern for the products he sells to arrive in excellent condition. The seller is friendly and communicates timely with his customers. I highly recommend this seller and would do business again anytime. Thank you.