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Item specifics

Condition
Good: A book that has been read but is in good condition. Very minimal damage to the cover including ...
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
Author
Charles W. Ostrom
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
Language
English
Publication Name
Time Series Analysis : Regression Techniques
Subject
Probability & Statistics / Regression Analysis, Research, Probability & Statistics / Time Series, Statistics
Publication Year
1990
Type
Textbook
Author
Charles W. Ostrom
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
Illustrated
Yes
Volume Number
Vol. 9
Dewey Decimal
300/.1/51955
Table Of Content
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
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., 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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