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

Year 2017, , 91 - 100, 09.10.2017
https://doi.org/10.30931/jetas.336853

Abstract

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.

References

  • [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
Year 2017, , 91 - 100, 09.10.2017
https://doi.org/10.30931/jetas.336853

Abstract

References

  • [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
There are 10 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Article
Authors

Didem Tetik Küçükelçi

Atıf Evren

Publication Date October 9, 2017
Published in Issue Year 2017

Cite

APA Tetik Küçükelçi, D., & Evren, A. (2017). A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models. Journal of Engineering Technology and Applied Sciences, 2(2), 91-100. https://doi.org/10.30931/jetas.336853
AMA Tetik Küçükelçi D, Evren A. A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models. JETAS. October 2017;2(2):91-100. doi:10.30931/jetas.336853
Chicago Tetik Küçükelçi, Didem, and Atıf Evren. “A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models”. Journal of Engineering Technology and Applied Sciences 2, no. 2 (October 2017): 91-100. https://doi.org/10.30931/jetas.336853.
EndNote Tetik Küçükelçi D, Evren A (October 1, 2017) A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models. Journal of Engineering Technology and Applied Sciences 2 2 91–100.
IEEE D. Tetik Küçükelçi and A. Evren, “A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models”, JETAS, vol. 2, no. 2, pp. 91–100, 2017, doi: 10.30931/jetas.336853.
ISNAD Tetik Küçükelçi, Didem - Evren, Atıf. “A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models”. Journal of Engineering Technology and Applied Sciences 2/2 (October 2017), 91-100. https://doi.org/10.30931/jetas.336853.
JAMA Tetik Küçükelçi D, Evren A. A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models. JETAS. 2017;2:91–100.
MLA Tetik Küçükelçi, Didem and Atıf Evren. “A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models”. Journal of Engineering Technology and Applied Sciences, vol. 2, no. 2, 2017, pp. 91-100, doi:10.30931/jetas.336853.
Vancouver Tetik Küçükelçi D, Evren A. A Comparison Between Mıcrosoft Excel Solver and Ncss, Spss Routines for Nonlinear Regression Models. JETAS. 2017;2(2):91-100.