Estimating the Coefficients of Polynomial Regression Model when the Error Distributed Generalized Logistic with Three Parameters

Authors

  • Ahmed Dheyab Ahmed Computer Center , College of Administration and Economics, University of Baghdad/Iraq Author
  • Ebtisam Karim Abdulah Computer Center , College of Administration and Economics, University of Baghdad/Iraq Author
  • Baydaa Ismael Abdulwahhab Computer Center , College of Administration and Economics, University of Baghdad/Iraq Author

DOI:

https://doi.org/10.61841/wafya217

Keywords:

Polynomial regression, Generalized Logistic distribution, Modified maximum likelihood method, General least squares, Mean square error

Abstract

In this research, estimates of polynomial regression model coefficients are derived when the random error is logistically distributed with three parameters representing scale, shape, and location. By employing the simulation method, the model coefficients are compared using the methods of general least squares and the modified maximum likelihood. Based on statistical criteria, the mean square error (MSE) indicated that the modified maximum likelihood (MML1) method is the best. This method is applied to data of Gross Domestic Product (GDP) at current prices in Iraq. 

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References

1. Ahmed, D.A., and Kadhim, G.A., (2017), Estimate coefficients multi-factor - a polynomial of the second degree regression with practical application." AL-Qadisiyah Journal, Baghdad,19,3.

2. Akkaya, A.D., and Tiku, M.L. (2008). "Robust estimation in multiple linear regression modelith non-Gaussian noise." Automatica 44, 407-417.

3. Akkaya, A.D., and Tiku, M.L. (2010). "Estimation in multifactor polynomial regression under nonnormality." Pak. J. Statist. Vol. 26(1), 49-68.

4. Braune, N., and Shacham,. (1998). "Identifying and removing sources of imprecision in polynomial regression." Mathematics and Computers in Simulation 48, 75±91.

5. Draper, N. R., and Smith, H. (1981). Applied Regression Analysis, Second Edition. John Wiley and Sons. New York.

6. Ebtisam, A., Ahmed, A., and Baydaa, A. (2019). Comparison of Estimate Methods of Multiple Linear Regression Model with Auto-Correlated Errors when the Error is Distributed with General Logistic. Journal of Engineering and Applied Sciences, V(14), N(19), PP 7072-7076 .

7. Islam, M.Q., and Tiku, M.L. (2004). "Multiple linear regression model under no normality." Commun. Stat.-Theory and Methods, 33, 2443-2467.

8. Ministry of Planning, Central Statistical Organization, Iraq.

9. Puthenpura, S., and Sinha, N.K. (1986). "Modified maximum likelihood method for the robust estimation of system parameters from very noisy data." Automatica, 22, 231-235.

10. Tiku, M.L. and Suresh, R.P. (1992). "A new method of estimation for location and scale parameters." J. Stat. Plan. Infer., 30, 281-292.

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Published

31.10.2020

Issue

Vol. 24 No. 8 (2020): 24 (8) 2020

Section

Articles

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Copyright (c) 2020 AUTHOR

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How to Cite

Dheyab Ahmed, A., Karim Abdulah, E., & Ismael Abdulwahhab, B. (2020). Estimating the Coefficients of Polynomial Regression Model when the Error Distributed Generalized Logistic with Three Parameters. International Journal of Psychosocial Rehabilitation, 24(8), 4487-4496. https://doi.org/10.61841/wafya217