An Application of Least Squares Method in Nonlinear Models–Solid Waste Sample

Year 2021, Volume: 6 Issue: 2, 71 - 75, 30.09.2021

Fatma Buğlem Yalçın

Abstract

Nowadays, the usage of nonlinear regression models is common. However, non-linear models
are more difficult to teach than linear models. The ordinary least squares method is effective in teaching
nonlinear regression models. In this study, it is aimed to teach the subjects of non-linear regression in
statistics for students. Transformed models are used for this. The ordinary least squares estimators of
models are obtained and the comparison of these is made. Besides, an explanatory application is made on
this subject.

Keywords

linear model, non-linear model, ordinary least squares, estimate.

References

• Arhipova I, Balina S. Problem of Choosing Statistical Hypotheses in Applied Statistics. 16th Symposium of IASC, Proceedings in Computational Statistics. 2004, 629 – 636.
• Arhipova I, Arhipovs S. Application of Ordinary Least Square Method in Nonlinear Models. International Statistical Institue. 2007, 56th Session,p.4.
• Birkes D, Dodge Y. Alternative Methods of Regression. John Wiley Sons. 1993, 80 – 140.
• Gujarati DN. Basic Econometrics. McGraw-Hill, Inc. 1995, 108 – 151.
• Gürünlü AÖ, Vupa Ö. Regresyon Analizinde Kullanılan En Küçük Kareler ve En Küçük Medyan Kareler Yöntemlerinin Karşılaştırılması. Süleyman Demirel Üniversitesi Fen Edebiyat Fakültesi Fen Dergisi (E-Dergi). 2, 2008, 219 – 229.
• Örün S, Karatekin C. İstanbul İli Avrupa Yakası İçin Uzun Dönem Elektrik Enerjisi Yük Tahmini. Elektrik-Elektronik-Bilgisayar ve Biyomedikal Muhendisliği Sempozyumu. 2014, 38 – 43.
• Wilcox RR. Introduction to Robust Estimation and Hypothesis Testing. Academic Press. 4(4), 1997, 2 – 21.
• Rencher AC, Schaalje GB. Linear Models in Statistics. John Wiley and Sons. 2008, 126 – 184.