Using Least squares methods and nonlinear regression Methods to Calculate the Approximate Value of Ionicity in Terms of the Energy Gap | Zendy

Ghassan E. Arif | Zendy; Sura Y. Jaafar | Zendy; Shymaa M. Abdullah | Zendy

Open Access

Using Least squares methods and nonlinear regression Methods to Calculate the Approximate Value of Ionicity in Terms of the Energy Gap

Author(s) -

Ghassan E. Arif,

Sura Y. Jaafar,

Shymaa M. Abdullah

Publication year - 2019

Publication title -

tikrit journal of pure science

Language(s) - English

Resource type - Journals

eISSN - 2415-1726

pISSN - 1813-1662

DOI - 10.25130/j.v24i5.874

Subject(s) - nonlinear regression , regression analysis , nonlinear system , quadratic equation , polynomial regression , mathematics , regression , value (mathematics) , energy (signal processing) , non linear least squares , statistics , least squares function approximation , explained sum of squares , physics , geometry , quantum mechanics , estimator

models to calculate the estimated value of the ionization for the physical compounds of semiconductors based on the energy gap throughout using some numerical analysis methods as the least squares method. The best of its branches obtained is a nonlinear method of the second degree, we compare the new result with other methods and we obtained our new method is more accurate and efficiency. Another side we using some regression analysis methods as the regression method. The best of its branches obtained is a nonlinear method of the quadratic regression model.

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