A Novel Regression Approach: Least Squares Ratio

Akbilgic, Oğuz; Akinci, Eylem

doi:10.1080/03610920802455076

A Novel Regression Approach: Least Squares Ratio

Akbilgic O., Akinci E. D.

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, cilt.38, sa.9, ss.1539-1545, 2009 (SCI-Expanded, Scopus)

Yayın Türü: Makale / Tam Makale
Cilt numarası: 38 Sayı: 9
Basım Tarihi: 2009
Doi Numarası: 10.1080/03610920802455076
Dergi Adı: COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
Sayfa Sayıları: ss.1539-1545
İstanbul Üniversitesi Adresli: Evet

Regression Analysis (RA) is one of the frequently used tool for forecasting. The Ordinary Least Squares (OLS) Technique is the basic instrument of RA and there are many regression techniques based on OLS. This paper includes a new regression approach, called Least Squares Ratio (LSR), and comparison of OLS and LSR according to mean square errors of estimation of theoretical regression parameters (mse ss) and dependent value (mse y).

Regression Analysis (RA) is one of the frequently used tool for forecasting. The

Ordinary Least Squares (OLS) Technique is the basic instrument of RA and there

are many regression techniques based on OLS. This paper includes a new regression

approach, called Least Squares Ratio (LSR), and comparison of OLS and LSR

according to mean square errors of estimation of theoretical regression parameters

(mse ß) and dependent value (mse y).