An ARIMA-Model-Based Approach to Seasonal Adjustment

Year 2008, Volume: 6 Issue: 1, 75 - 95, 15.07.2008

Kemal Çalık Seçil Çalık

Abstract

This article presents a model-based procedure to decompose a time series uniquely into mutually independent additive seasonal, trend, and irregular noise components. Estimators of components are calculated by Wiener-Kolmogrow (WK) filter. The series is assumed to follow the Gaussian ARIMA model. Properties of the procedure are discussed and an actual example is given. Demetra package programme was used at implementation.

Keywords

ARIMA model, Canonical decomposition, Signal extraction, Spectrum, Wiener- Kolmogrov filter

Mevsimsel Düzeltme için ARIMA Model Tabanlı Yaklaşım

Abstract

Bu makale, bir zaman serisini karşılıklı olarak birbirinden bağımsız mevsimsel, eğilim ve düzensiz bileşenlerine ayrıştırmak için ARIMA Model Tabanlı yaklaşım üzerinde durmaktadır. Bileşenlerin tahmin edicileri Wiener-Kolmogrov (WK) filtresi aracılığıyla hesaplanmaktadır. Serinin Gaussian ARIMA modeline sahip olduğu kabul edilmektedir. Yöntemin özellikleri açıklanmakta ve gerçek bir örnek verilmektedir. Uygulamada Demetra paket programı kullanılmıştır.

Keywords

ARIMA model, Kanonikal ayrıştırma, Sinyal çıkarımı, Spektrum, Wiener-Kolmogrov filtresi

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