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Forecasting with Dynamic Regression Models
One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives spec...
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Lenguaje: | eng |
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John Wiley & Sons
2012
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Acceso en línea: | http://cds.cern.ch/record/1438110 |
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author | Pankratz, Alan |
author_facet | Pankratz, Alan |
author_sort | Pankratz, Alan |
collection | CERN |
description | One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies. |
id | cern-1438110 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2012 |
publisher | John Wiley & Sons |
record_format | invenio |
spelling | cern-14381102021-04-22T00:31:19Zhttp://cds.cern.ch/record/1438110engPankratz, AlanForecasting with Dynamic Regression ModelsMathematical Physics and Mathematics One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.John Wiley & Sonsoai:cds.cern.ch:14381102012 |
spellingShingle | Mathematical Physics and Mathematics Pankratz, Alan Forecasting with Dynamic Regression Models |
title | Forecasting with Dynamic Regression Models |
title_full | Forecasting with Dynamic Regression Models |
title_fullStr | Forecasting with Dynamic Regression Models |
title_full_unstemmed | Forecasting with Dynamic Regression Models |
title_short | Forecasting with Dynamic Regression Models |
title_sort | forecasting with dynamic regression models |
topic | Mathematical Physics and Mathematics |
url | http://cds.cern.ch/record/1438110 |
work_keys_str_mv | AT pankratzalan forecastingwithdynamicregressionmodels |