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Time Series [Chapman & Hall/CRC Texts in Statistical Science]

Big River Books

(364104)

US $68.57

ApproximatelyS$ 90.83

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Located in: Powder Springs, Georgia, United States

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eBay item number:334774146302

Last updated on Jun 30, 2024 10:09:59 SGTView all revisionsView all revisions

Item specifics

Condition: Good: A book that has been read but is in good condition. Very minimal damage to the cover including ... 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 all condition definitionsopens in a new window or tab

ISBN: 9780367221096

Subject Area: Mathematics, Computers

Publication Name: Time Series : a Data Analysis Approach Using R

Publisher: CRC Press LLC

Item Length: 9.4 in

Subject: Programming Languages / General, Probability & Statistics / General, Probability & Statistics / Time Series

Publication Year: 2018

Series: Chapman and Hall/Crc Texts in Statistical Science Ser.

Type: Textbook

Format: Hardcover

Language: English

Item Height: 0.9 in

Author: David Stoffer, Robert Shumway

Item Weight: 15.3 Oz

Item Width: 6.4 in

Number of Pages: 272 Pages

About this product

Product Identifiers

Publisher

CRC Press LLC

ISBN-10

0367221098

ISBN-13

9780367221096

eBay Product ID (ePID)

2309310264

Product Key Features

Number of Pages

272 Pages

Language

English

Publication Name

Time Series : a Data Analysis Approach Using R

Publication Year

2018

Subject

Programming Languages / General, Probability & Statistics / General, Probability & Statistics / Time Series

Type

Textbook

Subject Area

Mathematics, Computers

Author

David Stoffer, Robert Shumway

Series

Chapman and Hall/Crc Texts in Statistical Science Ser.

Format

Hardcover

Dimensions

Item Height

0.9 in

Item Weight

15.3 Oz

Item Length

9.4 in

Item Width

6.4 in

Additional Product Features

Intended Audience

College Audience

LCCN

2019-018441

Reviews

"The intended audience of the book are mathematics undergraduates taking a one semester course on time series. . . The authors frame learning time series primarily by extending concepts from linear models. Personally, I favour this approach, since it allows the book to clearly signpost similarities and differences between concepts in both topics and provides a natural learning progression from what most undergraduate students will already be familiar with . . .This book successfully delivers a practical tool-based approach to time series analysis at an introductory level, complementing the existing texts from the authors, which are aimed at a more advanced audience." ~Matthew Nunes, Journal Times Series Analysis

CLASSIFICATION_METADATA

{"IsNonfiction":["No"],"IsOther":["No"],"IsAdult":["No"],"MuzeFormatDesc":["Hardcover"],"IsChildren":["No"],"Genre":["COMPUTERS","MATHEMATICS"],"Topic":["Probability & Statistics / Time Series","Probability & Statistics / General","Programming Languages / General"],"IsTextBook":["Yes"],"IsFiction":["No"]}

Illustrated

Yes

Table Of Content

1. Time Series Characteristics. 2. Time Series Regression and EDA. 3. ARIMA Models. 4. Spectral Analysis and Filtering. 5. Some Additional Topics.

Synopsis

This textbook is designed for an introductory time series course where the prerequisites are an understanding of linear regression and some basic probability skills. All of the numerical examples were done using the R statistical package, and the code is typically listed at the end of an example., The goals of this text are to develop the skills and an appreciation for the richness and versatility of modern time series analysis as a tool for analyzing dependent data. A useful feature of the presentation is the inclusion of nontrivial data sets illustrating the richness of potential applications to problems in the biological, physical, and social sciences as well as medicine. The text presents a balanced and comprehensive treatment of both time and frequency domain methods with an emphasis on data analysis. Numerous examples using data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and the analysis of economic and financial problems. The text can be used for a one semester/quarter introductory time series course where the prerequisites are an understanding of linear regression, basic calculus-based probability skills, and math skills at the high school level. All of the numerical examples use the R statistical package without assuming that the reader has previously used the software. Robert H. Shumway is Professor Emeritus of Statistics, University of California, Davis. He is a Fellow of the American Statistical Association and has won the American Statistical Association Award for Outstanding Statistical Application. He is the author of numerous texts and served on editorial boards such as the Journal of Forecasting and the Journal of the American Statistical Association . David S. Stoffer is Professor of Statistics, University of Pittsburgh. He is a Fellow of the American Statistical Association and has won the American Statistical Association Award for Outstanding Statistical Application. He is currently on the editorial boards of the Journal of Forecasting , the Annals of Statistical Mathematics , and the Journal of Time Series Analysis . He served as a Program Director in the Division of Mathematical Sciences at the National Science Foundation and as an Associate Editor for the Journal of the American Statistical Association and the Journal of Business & Economic Statistics .

LC Classification Number

QA280.S5845 2019

ebay_catalog_id

2019

Item description from the seller

Seller assumes all responsibility for this listing.

eBay item number:334774146302

Last updated on Jun 30, 2024 10:09:59 SGTView all revisionsView all revisions

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Powder Springs, Georgia, United States

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