Premium
Selection and estimation of component models for seasonal time series
Author(s) -
Haywood John,
Wilson Granville Tunnicliffe
Publication year - 2000
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/1099-131x(200009)19:5<393::aid-for755>3.0.co;2-6
Subject(s) - seasonality , series (stratigraphy) , residual , seasonal adjustment , econometrics , component (thermodynamics) , time series , estimation , model selection , selection (genetic algorithm) , statistics , computer science , mathematics , economics , algorithm , geology , artificial intelligence , variable (mathematics) , paleontology , physics , management , thermodynamics , mathematical analysis
We present a method for investigating the evolution of trend and seasonality in an observed time series. A general model is fitted to a residual spectrum, using components to represent the seasonality. We show graphically how well the fitted spectrum captures the evidence for evolving seasonality associated with the different seasonal frequencies. We apply the method to model two time series and illustrate the resulting forecasts and seasonal adjustment for one series. Copyright © 2000 John Wiley & Sons, Ltd.