تقدير أنموذجي Logistic و Gompertz لدراسة نمو صادرات النفط في العراق للفترة (2009-2010)‎

Abstract EN

Estimating the parameters of nonlinear models is one of the most important things to calculate in nonlinear regression to see how models respond to research data.

Several nonlinear models have been used to describe a particular growth, e.g.

Logistic model and Gompertz model.

The Nonlinear Least Squares Method is a common way of estimating parameters through the Gauss-Newton algorithm, as well as the simplicity and ease of the method of solving several problems.

The maximal posterior method.

The aim of the research is to compare two estimation methods using some statistical indicators, such as mean error squares and the coefficient of selection.

The study showed that the Nonlinear Least Squares method is better than the maximal A posteriori method because it possesses the least MSE