Forecasting Aggregated Vector ARMA Processes

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Last edited by AgentSapphire
August 5, 2023 | History

Forecasting Aggregated Vector ARMA Processes

  • 1 Want to read

This study is concerned with forecasting time series variables and the impact of the level of aggregation on the efficiency of the forecasts. Since temporally and contemporaneously disaggregated data at various levels have become available for many countries, regions, and variables during the last decades the question which data and procedures to use for prediction has become increasingly important in recent years. This study aims at pointing out some of the problems involved and at pro­ viding some suggestions how to proceed in particular situations. Many of the results have been circulated as working papers, some have been published as journal articles, and some have been presented at conferences and in seminars. I express my gratitude to all those who have commented on parts of this study. They are too numerous to be listed here and many of them are anonymous referees and are therefore unknown to me. Some early results related to the present study are contained in my monograph "Prognose aggregierter Zeitreihen" (Lutkepohl (1986a)) which was essentially completed in 1983. The present study contains major extensions of that research and also summarizes the earlier results to the extent they are of interest in the context of this study.
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Publish Date
Publisher
Springer
Language
English
Pages
333

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Previews available in: English

Edition Availability
Cover of: Forecasting Aggregated Vector ARMA Processes
Forecasting Aggregated Vector ARMA Processes
2012, Springer
in English
Cover of: Forecasting Aggregated Vector ARMA Processes
Forecasting Aggregated Vector ARMA Processes
1987, Springer
paperback in English
Cover of: Forecasting Aggregated Vector ARMA Processes
Forecasting Aggregated Vector ARMA Processes
1987, Springer-Verlag
Paperback in English

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Book Details


Edition Notes

Source title: Forecasting Aggregated Vector ARMA Processes (Lecture Notes in Economics and Mathematical Systems, 284)

Classifications

Library of Congress
HB139-141

The Physical Object

Format
paperback
Number of pages
333

ID Numbers

Open Library
OL32869605M
Internet Archive
forecastingaggre0000lutk
ISBN 10
3540172084
ISBN 13
9783540172086

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History

Download catalog record: RDF / JSON
August 5, 2023 Edited by AgentSapphire Merge works
December 4, 2022 Edited by ImportBot import existing book
July 27, 2019 Edited by Lisa Edited without comment.
July 27, 2019 Edited by Lisa Added new cover
December 9, 2009 Created by WorkBot add works page