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Selection and estimation of component models for seasonal time series.

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Selection and estimation of component models for seasonal time series. / Haywood, John; Tunnicliffe Wilson, Granville.
In: Journal of Forecasting, Vol. 19, No. 5, 09.2000, p. 393-417.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Haywood, J & Tunnicliffe Wilson, G 2000, 'Selection and estimation of component models for seasonal time series.', Journal of Forecasting, vol. 19, no. 5, pp. 393-417. https://doi.org/10.1002/1099-131X(200009)19:5<393::AID-FOR755>3.0.CO;2-6

APA

Haywood, J., & Tunnicliffe Wilson, G. (2000). Selection and estimation of component models for seasonal time series. Journal of Forecasting, 19(5), 393-417. https://doi.org/10.1002/1099-131X(200009)19:5<393::AID-FOR755>3.0.CO;2-6

Vancouver

Haywood J, Tunnicliffe Wilson G. Selection and estimation of component models for seasonal time series. Journal of Forecasting. 2000 Sept;19(5):393-417. doi: 10.1002/1099-131X(200009)19:5<393::AID-FOR755>3.0.CO;2-6

Author

Haywood, John ; Tunnicliffe Wilson, Granville. / Selection and estimation of component models for seasonal time series. In: Journal of Forecasting. 2000 ; Vol. 19, No. 5. pp. 393-417.

Bibtex

@article{3b3ab13f65ca4edc899fea52d4e6a67f,
title = "Selection and estimation of component models for seasonal time series.",
abstract = "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.",
keywords = "seasonal time series, evolving seasonality, spectrum components, frequency domain estimation",
author = "John Haywood and {Tunnicliffe Wilson}, Granville",
year = "2000",
month = sep,
doi = "10.1002/1099-131X(200009)19:5<393::AID-FOR755>3.0.CO;2-6",
language = "English",
volume = "19",
pages = "393--417",
journal = "Journal of Forecasting",
issn = "0277-6693",
publisher = "John Wiley and Sons Ltd",
number = "5",

}

RIS

TY - JOUR

T1 - Selection and estimation of component models for seasonal time series.

AU - Haywood, John

AU - Tunnicliffe Wilson, Granville

PY - 2000/9

Y1 - 2000/9

N2 - 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.

AB - 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.

KW - seasonal time series

KW - evolving seasonality

KW - spectrum components

KW - frequency domain estimation

U2 - 10.1002/1099-131X(200009)19:5<393::AID-FOR755>3.0.CO;2-6

DO - 10.1002/1099-131X(200009)19:5<393::AID-FOR755>3.0.CO;2-6

M3 - Journal article

VL - 19

SP - 393

EP - 417

JO - Journal of Forecasting

JF - Journal of Forecasting

SN - 0277-6693

IS - 5

ER -