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, vol.38, no.9, pp.1539-1545, 2009 (SCI-Expanded, Scopus)

Publication Type: Article / Article
Volume: 38 Issue: 9
Publication Date: 2009
Doi Number: 10.1080/03610920802455076
Journal Name: COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
Page Numbers: pp.1539-1545
Istanbul University Affiliated: Yes

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).