An ARIMA-Model-Based Approach to Seasonal Adjustment

Yıl 2008, Cilt: 6 Sayı: 1, 75 - 95, 15.07.2008

Kemal Çalık Seçil Çalık

Öz

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.

Anahtar Kelimeler

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

Mevsimsel Düzeltme için ARIMA Model Tabanlı Yaklaşım

Öz

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.

Anahtar Kelimeler

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

Kaynakça

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