Benchmarking Temporal Distribution And Reconciliation Methods For Time Series 2006 Edition at Meripustak

Benchmarking Temporal Distribution And Reconciliation Methods For Time Series 2006 Edition

Books from same Author: Estela Bee Dagum Pierre A. Cholette

Books from same Publisher: Springer

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  • General Information  
    Author(s)Estela Bee Dagum Pierre A. Cholette
    PublisherSpringer
    ISBN9780387311029
    Pages410
    BindingPaperback
    LanguageEnglish
    Publish YearMay 2006

    Description

    Springer Benchmarking Temporal Distribution And Reconciliation Methods For Time Series 2006 Edition by Estela Bee Dagum Pierre A. Cholette

    Time series play a crucial role in modern economies at all levels of activity and are used by decision makers to plan for a better future. Before publication time series are subject to statistical adjustments and this is the first statistical book to systematically deal with the methods most often applied for such adjustments. Regression-based models are emphasized because of their clarity ease of application and superior results. Each topic is illustrated with real case examples. In order to facilitate understanding of their properties and limitations of the methods discussed a real data example is followed throughout the book. Table of contents : The Components of Time Series.- The Cholette-Dagum Regression-Based Benchmarking Method - The Additive Model.- Covariance Matrices for Benchmarking and Reconciliation Methods.- The Cholette-Dagum Regression-Based Benchmarking Method - The Multiplicative Model.- The Denton Method and its Variants.- Temporal Distribution Interpolation and Extrapolation.- Signal Extraction and Benchmarking.- Calendarization.- A Unified Regression-Based Framework for Signal Extraction Benchmarking and Interpolation.- Reconciliation and Balancing Systems of Time Series.- Reconciling One-Way Classified Systems of Time Series.- Reconciling the Marginal Totals of Two-Way Classified Systems of Series.- Reconciling Two-Way Classifed Systems of Series.