A novel regression approach: Least squares ratio

Oguz Akbilgic, Eylem Deniz Akinci

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

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).

Original languageEnglish (US)
Pages (from-to)1539-1545
Number of pages7
JournalCommunications in Statistics - Theory and Methods
Volume38
Issue number9
DOIs
StatePublished - Jan 1 2009

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Ordinary Least Squares
Least Squares
Regression
Regression Analysis
Mean square error
Forecasting
Dependent

All Science Journal Classification (ASJC) codes

  • Statistics and Probability

Cite this

A novel regression approach : Least squares ratio. / Akbilgic, Oguz; Akinci, Eylem Deniz.

In: Communications in Statistics - Theory and Methods, Vol. 38, No. 9, 01.01.2009, p. 1539-1545.

Research output: Contribution to journalArticle

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