A dissertation in the College of Administration and Economics at the University of Karbala discussed “Bayes estimator in cubic slices using the digital algorithm to estimate the fuzzy regression function with a practical application.”
The study titled (Baez estimator in cubic slices using the digital algorithm to estimate the fuzzy regression function with a practical application) by student Zainab Hassan Radhi Al-Khafaji included the use of fuzzy non-parametric regression models in estimating the non-parametric regression function and the suggestion of two different methods that adopt the use of smoothing methods for cubic slices in the Bayes estimator
The study aimed to construct a fuzzy nonparametric regression model when the independent variables do not have a definite functional form.
The study reached a set of results, the most important of which is that the use of the Bayesian linear regression formula and the focused sampling method were two effective methods in finding an estimate of the fuzzy nonparametric regression function in two cases, which are the case of normal distribution of random errors and the case of contamination in random errors.
The study recommended the use of polynomial regression model, which was more suitable in representing the data
