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Time Series Analysis: Vol. 9 Regression Techniques.

Author: Charles W Ostrom; Sage Publications.
Publisher: Thousand Oaks : SAGE Publications, Incorporated Jan. 1990.
Series: Quantitative Applications in the Social Sciences Ser., vol. 9.
Edition/Format:   eBook : Document : English : 2nd edView all editions and formats
Summary:
Annotation

The great advantage of time series regression analysis is that it can both explain the past and predict the future behaviour 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 partially bridge the gap between the two approaches.

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Details

Genre/Form: Electronic book
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Charles W Ostrom; Sage Publications.
ISBN: 0803931352 9780803931350
OCLC Number: 1066601085
Target Audience: Scholarly & Professional
Description: 1 online resource (96 pages) illustrations.
Contents: IntroductionTime Series Regression Analysis Nonlagged CaseA Ratio Goal HypothesisThe Error TermTime Series Regression ModelNonautoregression AssumptionConsequences of Violating the Nonautoregression AssumptionConventional Tests for AutocorrelationAn Alternative Method of EstimationEGLS Estimation (First-Order Autocorrelation)Small Sample PropertiesThe Ratio Goal Hypothesis ReconsideredExtension to Multiple RegressionConclusionAlternative Time-Dependent ProcessesAlternative ProcessesTesting for Higher Order ProcessesProcess IdentificationEstimationExample Estimation of Models with Errors Generated by Alternative Time Dependent ProcessesExample Ratio Goal Model ReconsideredConclusionTime Series Regression Analysis Lagged CaseDistributed Lag ModelsLagged Endogenous VariablesTesting for Autocorrelation in Models with Lagged Endogenous VariablesEstimationEGLA EstimationExampleA Revised Ratio Goal ModelInterpreting Distributed Lag ModelsConclusionForecastingForecast ErrorForecast GenerationModifying the Forecast EquationForecast EvaluationExampleConclusionSummary
Series Title: Quantitative Applications in the Social Sciences Ser., vol. 9.
Other Titles: Time Series Analysis:

Abstract:

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)  Read more...

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