A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models

Yıl 2017, Cilt: 2 Sayı: 2, 91 - 100, 09.10.2017

Didem Tetik Küçükelçi Atıf Evren

https://doi.org/10.30931/jetas.336853

Öz

In this study we have tried to compare the results obtained by Microsoft Excel Solver program with those of NCSS and SPSS in some nonlinear regression models. We fit some nonlinear models to data present in http//itl.nist.gov/div898/strd/nls/nls_main.shtml by the three packages. Although EXCEL did not succeed as well as the other packages, we conclude that Microsoft Excel Solver provides us a cheaper and a more interactive way of studying nonlinear models.

Anahtar Kelimeler

Non-Linear Regression, SPSS, NCSS

Kaynakça

• [1] Bates, D.M., Watts, D.G., Nonlinear Regression Analysis and Its Applications, New York, John Wiley&Sons, (1988).
• [2] Bevington,P.R., Robinson,D.K., “Data Reduction and Error Analysis for the Physical Sciences”, McGraw Hill, Third edition, (2003) 148-151.
• [3] Billo, E.J., EXCEL for Scientists and Engineers Numerical Methods,Wiley- Interscience, John Wiley&Sons, (2007).
• [4] De Levie, R., Advanced Excel for Scientific Data Analysis, Oxford University Press, (2004).
• [5] Huet,S., Bouvier,A., Gruet,M., Jolivet,E., Statistical Tools for Nonlinear Regression: A Practical Guide with S-Plus Examples, Springer-Verlag, New York, Springer Series in Statistics, (1996).
• [6] Motulsky, H., Christopoulos, A., Fitting Models to Biological Data Using Linear and Nonlinear Regression: A Practical Guide to Curve Fitting, USA, Oxford University Press, (2004).
• [7] Neter J., Wasserman W., Kutner M. H., “Applied Linear Statistical Models”, Second edition,Illinois, Richard D. Irwin. (1985). 466-490.
• [8] Ross, G.J.S., Nonlinear Estimation, Springer Series in Statistics , Springer-Verlag, (1990).
• [9] Seber G.A.F., WILD C.J., “Nonlinear Regression”, USA, John Wiley&Sons., (1989) 91-102.
• [10] http//itl.nist.gov/div898/strd/nls/nls_main.shtml