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Economic time series : modeling and seasonality
[NT 42944] Record Type:
[NT 8598] Electronic resources : [NT 40817] monographic
[NT 47348] Title Information:
modeling and seasonality
[NT 47354] Secondary Intellectual Responsibility:
BellWilliam R., 1943-
[NT 47354] Secondary Intellectual Responsibility:
HolanScott H.,
[NT 47354] Secondary Intellectual Responsibility:
McElroyTucker,
[NT 47351] Place of Publication:
Boca Raton, FL
[NT 47263] Published:
CRC Press;
[NT 47352] Year of Publication:
2012
[NT 47264] Description:
1 online resource
[NT 47266] Subject:
Seasonal variations (Economics) - Mathematical models -
[NT 47266] Subject:
Time-series analysis - Mathematical models -
[NT 47266] Subject:
Econometrics -
[NT 47266] Subject:
Economics, Mathematical -
[NT 47266] Subject:
Economics -
[NT 47266] Subject:
Seasons -
[NT 47266] Subject:
Models, Econometric -
[NT 51458] Online resource:
http://www.crcnetbase.com/isbn/9781439846582
[NT 47265] Notes:
Print version record
[NT 51398] Summary:
Economic Time Series: Modeling and Seasonality is a focused resource on analysis of economic time series as pertains to modeling and seasonality, presenting cutting-edge research that would otherwise be scattered throughout diverse peer-reviewed journals. This compilation of 21 chapters showcases the cross-fertilization between the fields of time series modeling and seasonal adjustment, as is reflected both in the contents of the chapters and in their authorship, with contributors coming from academia and government statistical agencies. For easier perusal and absorption, the contents have been
[NT 50961] ISBN:
9781439846582electronic bk.
[NT 50961] ISBN:
1439846588electronic bk.
[NT 60779] Content Note:
Front Cover; Contents; Preface; Editors; Contributors; Part I: Periodic Modeling of Economic Time Series; 1. A Multivariate Periodic Unobserved Components Time Series Analysis for Sectoral U.S. Employment; 2. Seasonal Heteroskedasticity in Time Series Data: Modeling, Estimation, and Testing; 3. Choosing Seasonal Autocovariance Structures: PARMA or SARMA?; Part II: Estimating Time Series Components with Misspecified Models; 4. Specification and Misspecification of Unobserved Components Models; 5. Error in Business Cycle Estimates Obtained from Seasonally Adjusted Data
Economic time series : modeling and seasonality
Economic time series
: modeling and seasonality / [edited by] William R. Bell, Scott H. Holan, and Tucker S. McElroy - Boca Raton, FL : CRC Press, 2012. - 1 online resource.
Front Cover; Contents; Preface; Editors; Contributors; Part I: Periodic Modeling of Economic Time Series; 1. A Multivariate Periodic Unobserved Components Time Series Analysis for Sectoral U.S. Employment; 2. Seasonal Heteroskedasticity in Time Series Data: Modeling, Estimation, and Testing; 3. Choosing Seasonal Autocovariance Structures: PARMA or SARMA?; Part II: Estimating Time Series Components with Misspecified Models; 4. Specification and Misspecification of Unobserved Components Models; 5. Error in Business Cycle Estimates Obtained from Seasonally Adjusted Data.
Print version record.
Includes bibliographical references and index.
ISBN 9781439846582ISBN 1439846588
Seasonal variations (Economics)Time-series analysisEconometricsEconomics, MathematicalEconomicsSeasonsModels, Econometric -- Mathematical models -- Mathematical models
Bell, William R.
Economic time series : modeling and seasonality
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Front Cover; Contents; Preface; Editors; Contributors; Part I: Periodic Modeling of Economic Time Series; 1. A Multivariate Periodic Unobserved Components Time Series Analysis for Sectoral U.S. Employment; 2. Seasonal Heteroskedasticity in Time Series Data: Modeling, Estimation, and Testing; 3. Choosing Seasonal Autocovariance Structures: PARMA or SARMA?; Part II: Estimating Time Series Components with Misspecified Models; 4. Specification and Misspecification of Unobserved Components Models; 5. Error in Business Cycle Estimates Obtained from Seasonally Adjusted Data
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Economic Time Series: Modeling and Seasonality is a focused resource on analysis of economic time series as pertains to modeling and seasonality, presenting cutting-edge research that would otherwise be scattered throughout diverse peer-reviewed journals. This compilation of 21 chapters showcases the cross-fertilization between the fields of time series modeling and seasonal adjustment, as is reflected both in the contents of the chapters and in their authorship, with contributors coming from academia and government statistical agencies. For easier perusal and absorption, the contents have been
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http://www.crcnetbase.com/isbn/9781439846582
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