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An Introduction to Time Series Analysis and Forecasting: With Applications of...
by Yaffee, Robert A.; McGee, Monnie | HC | VeryGood
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所在地：Aurora, Illinois, 美國
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估計於 8月8日, 四至 8月10日, 六之間送達 運送地點 84606
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物品細節
- 物品狀況
- 很好
- 賣家備註
- Binding
- Hardcover
- Weight
- 2 lbs
- Product Group
- Book
- IsTextBook
- Yes
- ISBN
- 9780127678702
- Subject Area
- Mathematics, Social Science
- Publication Name
- Introduction to Time Series Analysis and Forecasting : with Applications of Sas® and SPSS®
- Publisher
- Elsevier Science & Technology
- Item Length
- 9 in
- Subject
- Sociology / General, Probability & Statistics / General, General, Probability & Statistics / Time Series
- Publication Year
- 2000
- Type
- Textbook
- Format
- Hardcover
- Language
- English
- Item Height
- 0.5 in
- Item Weight
- 30.3 Oz
- Item Width
- 6 in
- Number of Pages
- 528 Pages
關於產品
Product Identifiers
Publisher
Elsevier Science & Technology
ISBN-10
0127678700
ISBN-13
9780127678702
eBay Product ID (ePID)
965556
Product Key Features
Number of Pages
528 Pages
Publication Name
Introduction to Time Series Analysis and Forecasting : with Applications of Sas® and SPSS®
Language
English
Subject
Sociology / General, Probability & Statistics / General, General, Probability & Statistics / Time Series
Publication Year
2000
Type
Textbook
Subject Area
Mathematics, Social Science
Format
Hardcover
Dimensions
Item Height
0.5 in
Item Weight
30.3 Oz
Item Length
9 in
Item Width
6 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
99-062662
TitleLeading
An
Reviews
"Robert Yaffee has performed an invaluable service to students of time series analysis by preparing an introduction to methods for analyzing time series data that includes examples drawn from the social sciences, and demonstrates how to program the procedures in SPSS and SAS. Introduction to Time Series Analysis and Forecasting will be a standard reference for years to come." --DAVID F. GREENBERG, New York University, New York, From the prepublication reviews "Robert Yaffee has performed an invaluable service to students of time series analysis by preparing an introduction to methods for analysing time series data that includes examples drawn from the social sciences, and demonstrates how to program the procedures in SPSS and SAS. Introduction to Time Series Analysis and Forecasting will be a standard reference for years to come." -DAVID F. GREENBERG, New York University, New York
Illustrated
Yes
Table Of Content
Preface. Introduction and Overview. Extrapolative Models and Decomposition Models. Introduction to Box-Jenkins Time Series Analysis. The Basic ARIMA Model. Seasonal ARIMA Models. Estimation and Diagnosis. Metadiagnosis and Forecasting. Intervention Analysis. Transfer Function Models. Autoregressive Error Models. A Review of Model and Forecast Evaluation. M. McGee , Power Analysis and Sample Size Determination for Well-Known Time Series Models. Appendix A. Glossary. Index.
Synopsis
Providing a clear explanation of the fundamental theory of time series analysis and forecasting, this book couples theory with applications of two popular statistical packages--SAS and SPSS. The text examines moving average, exponential smoothing, Census X-11 deseasonalization, ARIMA, intervention, transfer function, and autoregressive error models and has brief discussions of ARCH and GARCH models. The book features treatments of forecast improvement with regression and autoregression combination models and model and forecast evaluation, along with a sample size analysis for common time series models to attain adequate statistical power. The careful linkage of the theoretical constructs with the practical considerations involved in utilizing the statistical packages makes it easy for the user to properly apply these techniques., Providing a clear explanation of the fundamental theory of time series analysis and forecasting, this book couples theory with applications of two popular statistical packages--SAS and SPSS. The text examines moving average, exponential smoothing, Census X-11 deseasonalization, ARIMA, intervention, transfer function, and autoregressive error models and has brief discussions of ARCH and GARCH models. The book features treatments of forecast improvement with regression and autoregression combination models and model and forecast evaluation, along with a sample size analysis for common time series models to attain adequate statistical power. The careful linkage of the theoretical constructs with the practical considerations involved in utilizing the statistical packages makes it easy for the user to properly apply these techniques. Describes principal approaches to time series analysis and forecasting Presents examples from public opinion research, policy analysis, political science, economics, and sociology Math level pitched to general social science usage Glossary makes the material accessible for readers at all levels
LC Classification Number
HA30.3.Y34 2000
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物品所在地：
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