Investigation of goose breeding in Turkiye by linear and nonlinear regression models

Abstract

In this study, the change in the number of geese breeding in Turkiye over the years was examined by linear and non-linear regression models. Among linear and non-linear regression models, linear, quadratic, cubic, logarithmic, and inverse regression models were used. R2 and MSE values were taken as criteria for comparing the models. As a result of the study, the cubic regression model with the highest R2 value and the lowest MSE value was found to be the best fitting model for the number of geese. According to the cubic regression model, the number of geese in Turkiye in 2023 and 2024 was estimated to be 1849304 and 2107588, respectively.