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Time Series Analysis: Regression Te..., Ostrom, Dr. Cha
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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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Item specifics
- Condition
- Book Title
- Time Series Analysis: Regression Techniques: 9 (Quantitative A...
- ISBN
- 0803931352
- EAN
- 9780803931350
- Date of Publication
- 19900313
- Release Title
- Time Series Analysis: Regression Techniques: 9 (Quantitative A...
- Artist
- Ostrom, Dr. Charles W.
- Brand
- N/A
- Colour
- N/A
- Subject Area
- Mathematics, Social Science
- Publication Name
- Time Series Analysis : Regression Techniques
- Publisher
- SAGE Publications, Incorporated
- Item Length
- 8.4 in
- Subject
- Probability & Statistics / Regression Analysis, Research, Probability & Statistics / Time Series, Statistics
- Publication Year
- 1990
- Series
- Quantitative Applications in the Social Sciences Ser.
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Item Height
- 0.3 in
- Item Weight
- 4 Oz
- Item Width
- 5.3 in
- Number of Pages
- 96 Pages
About this product
Product Identifiers
Publisher
SAGE Publications, Incorporated
ISBN-10
0803931352
ISBN-13
9780803931350
eBay Product ID (ePID)
1144265
Product Key Features
Number of Pages
96 Pages
Publication Name
Time Series Analysis : Regression Techniques
Language
English
Publication Year
1990
Subject
Probability & Statistics / Regression Analysis, Research, Probability & Statistics / Time Series, Statistics
Type
Textbook
Subject Area
Mathematics, Social Science
Series
Quantitative Applications in the Social Sciences Ser.
Format
Trade Paperback
Dimensions
Item Height
0.3 in
Item Weight
4 Oz
Item Length
8.4 in
Item Width
5.3 in
Additional Product Features
Edition Number
2
Intended Audience
Scholarly & Professional
LCCN
89-010715
Dewey Edition
20
Series Volume Number
9
Volume Number
Vol. 9
Illustrated
Yes
Dewey Decimal
300/.1/51955
Table Of Content
Introduction Time Series Regression Analysis Nonlagged Case A Ratio Goal Hypothesis The Error Term Time Series Regression Model Nonautoregression Assumption Consequences of Violating the Nonautoregression Assumption Conventional Tests for Autocorrelation An Alternative Method of Estimation EGLS Estimation (First-Order Autocorrelation) Small Sample Properties The Ratio Goal Hypothesis Reconsidered Extension to Multiple Regression Conclusion Alternative Time-Dependent Processes Alternative Processes Testing for Higher Order Processes Process Identification Estimation Example Estimation of Models with Errors Generated by Alternative Time Dependent Processes Example Ratio Goal Model Reconsidered Conclusion Time Series Regression Analysis Lagged Case Distributed Lag Models Lagged Endogenous Variables Testing for Autocorrelation in Models with Lagged Endogenous Variables Estimation EGLA Estimation Example A Revised Ratio Goal Model Interpreting Distributed Lag Models Conclusion Forecasting Forecast Error Forecast Generation Modifying the Forecast Equation Forecast Evaluation Example Conclusion Summary
Synopsis
"The text gives a good basis for understanding the ideas of the time series models and estimation, without overwhelming readers with the complexity of the subject." --Journal of the American Statistical Association Completely revised and updated, this second edition of Time Series Analysis examines techniques for the study of change based on regression analysis. Ostrom demonstrates how these regression techniques may be employed for hypothesis testing, estimating, and forecasting. In addition, analysis strategies for both lagged and nonlagged models are presented and alternative time-dependent processes are explored., This volume explores the regression (or structural equation) approach to the analysis of time series data in which the modeller makes an initial specification of a causal structure and then analyzes the data to determine whether there is any empirical support for the specification. The great advantage of time series regression analysis is the possibility for both explaining the past, and predicting the future behaviour of variables of interest. Although this volume does not cover Box-Jenkins types of models for explaining endogenous variables, it does introduce the Box-Jenkins time series method as an alternative to modelling the underlying error processes. As such, the book attempts to partially bridge the gap between the two approaches to the analysis of time to time series data., The great advantage of time series regression analysis is that it can both explain the past and predict the future behavior of variables. This volume explores the regression (or structural equation) approach to the analysis of time series data. It also introduces the Box-Jenkins time series method in an attempt to bridge partially the gap between the two approaches.
LC Classification Number
HA30.3.O88 1990
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- e***a (53)- Feedback left by buyer.Past monthVerified purchaseLove the book, reasonably priced, exactly as described, quick shipping, well packed and excellent communication. A+ eBay seller. Thank you so very much. Most definitely will buy again.
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