AUTHOR(S): Taiwo Abass Ishola, Olatayo Timothy Olabisi, Adesanya Kazeem Kehinde

TITLE Parameter Estimation of Fractional Trigonometric Polynomial Regression Model 
ABSTRACT Fractional Trigonometric Polynomial Regression is a form of nonlinear regression in which the relationship between the outcome variable and risk variable is modelled as 1/nth degree polynomial regression by combining the function of sin(nx) and cos(nx) on the value of natural numbers. The model was used to analyse the relationship between three continuous and periodic variables. Coefficients of the model were estimated using the Maximum Likelihood Estimate (MLE) method. From the results, the model obtained indicated that an increased in body mass index will increase the level of blood pressure while age may or may not have an influence on the blood pressure level. The values of Coefficient of variation (R^2) showed the variation in the dependent variable was well explained by the independent variables and the value of adjusted (R^2) showed the model had a good fit with a high level of predictive power. 
KEYWORDS Genetic code, optimality, Heuristic methodsFractional regression, Polynomial, Trigonometric function, Periodic variation, Continuous variable 

Cite this paper Taiwo Abass Ishola, Olatayo Timothy Olabisi, Adesanya Kazeem Kehinde. (2020) Parameter Estimation of Fractional Trigonometric Polynomial Regression Model. International Journal of Computers, 5, 1924 
