Approaches to the construction of nonlinear models in fuzzy environment
Dilnoz Muhamediyeva, J Sayfiyev · Journal of Physics Conference Series · 2019
Abstract The Bayesian methods to the problems of statistical estimation when building nonlinear models are considered. Bayesian methods can be used to construct linear and nonlinear regression models with non-Gaussian laws for the distribution of probabilities of random observation errors. We consider continuous and discrete processes that can be described by statistical models. For this purpose, a description of computational Bayesian procedures and recommendations for the construction of nonlinear regression models are given introduction.