Using Johnson schumacher model for parameter estimation of nonlinear regression model

Abstract EN

In this study,
we aim to estimate parameters of nonlinear model by using ordinary least square.

This paper used a real data set on exchange rate, inflation, exports, imports, investments, and budget deficit.

The appropriate models of the data are cubic and Johnson Schumacher Model.

Both Results of application data and Simulation study appear that the Johnson Schumacher nonlinear regression model is outstanding performance
This paper develops the reliable alternative approach of parameter estimation based on the PSO algorithm in the model of nonlinear regression.

When the PSO method is used for estimating of nonlinear regression model parameters.

Estimating (Forecasting) of the exchange rate using Johnson Schumacher nonlinear model
This study presents the following variables: (X1: inflation), (X2: exports), (X3: imports), (X4: investments), (X5: budget deficit).

These represent the main variables that affect (Y: exchange rate).

The study introduced two nonlinear models cubic and Johnson Schumacher nonlinear model.

The Johnson Schumacher nonlinear model shows outstanding performance.

The results of the simulation