A KALMAN FILTER APPROACH TO THE FORECASTING OF MONTHLY TIME SERIES AFFECTED BY Morris Festivals

N. D. Morris; D. Pfeffermann

doi:10.1111/j.1467-9892.1984.tb00391.x

A KALMAN FILTER APPROACH TO THE FORECASTING OF MONTHLY TIME SERIES AFFECTED BY Morris Festivals

N. D. Morris^*
, D. Pfeffermann

^*Corresponding author for this work

Department of Statistics

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

Abstract. Many economic time series are affected by the moving dates of festivals. In this paper a moving festival effect is defined and incorporated into a dynamic linear model which specifies how the parameters of several unobservable components of a time series evolve stochastically in time. The merits of this approach in comparison to other approaches are discussed and demonstrated using empirical data of three selected time series.

Original language	English
Pages (from-to)	255-268
Number of pages	14
Journal	Journal of Time Series Analysis
Volume	5
Issue number	4
DOIs	https://doi.org/10.1111/j.1467-9892.1984.tb00391.x
State	Published - Jul 1984

Keywords

Dynamic linear models
Kalman filter
decomposition models
moving festival effects

Access to Document

10.1111/j.1467-9892.1984.tb00391.x

Cite this

@article{2f1ff00b6d4d46ccad1f09c43fea0474,

title = "A KALMAN FILTER APPROACH TO THE FORECASTING OF MONTHLY TIME SERIES AFFECTED BY Morris Festivals",

abstract = "Abstract. Many economic time series are affected by the moving dates of festivals. In this paper a moving festival effect is defined and incorporated into a dynamic linear model which specifies how the parameters of several unobservable components of a time series evolve stochastically in time. The merits of this approach in comparison to other approaches are discussed and demonstrated using empirical data of three selected time series.",

keywords = "Dynamic linear models, Kalman filter, decomposition models, moving festival effects",

author = "Morris, \{N. D.\} and D. Pfeffermann",

year = "1984",

month = jul,

doi = "10.1111/j.1467-9892.1984.tb00391.x",

language = "אנגלית",

volume = "5",

pages = "255--268",

journal = "Journal of Time Series Analysis",

issn = "0143-9782",

publisher = "Wiley-Blackwell",

number = "4",

}

TY - JOUR

T1 - A KALMAN FILTER APPROACH TO THE FORECASTING OF MONTHLY TIME SERIES AFFECTED BY Morris Festivals

AU - Morris, N. D.

AU - Pfeffermann, D.

PY - 1984/7

Y1 - 1984/7

N2 - Abstract. Many economic time series are affected by the moving dates of festivals. In this paper a moving festival effect is defined and incorporated into a dynamic linear model which specifies how the parameters of several unobservable components of a time series evolve stochastically in time. The merits of this approach in comparison to other approaches are discussed and demonstrated using empirical data of three selected time series.

AB - Abstract. Many economic time series are affected by the moving dates of festivals. In this paper a moving festival effect is defined and incorporated into a dynamic linear model which specifies how the parameters of several unobservable components of a time series evolve stochastically in time. The merits of this approach in comparison to other approaches are discussed and demonstrated using empirical data of three selected time series.

KW - Dynamic linear models

KW - Kalman filter

KW - decomposition models

KW - moving festival effects

UR - https://www.scopus.com/pages/publications/84986805582

U2 - 10.1111/j.1467-9892.1984.tb00391.x

DO - 10.1111/j.1467-9892.1984.tb00391.x

M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???

AN - SCOPUS:84986805582

SN - 0143-9782

VL - 5

SP - 255

EP - 268

JO - Journal of Time Series Analysis

JF - Journal of Time Series Analysis

IS - 4

ER -

A KALMAN FILTER APPROACH TO THE FORECASTING OF MONTHLY TIME SERIES AFFECTED BY Morris Festivals

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this