Using Johnson Schumacher Model for Parameter Estimation of Nonlinear Regression Model | ||||
| مجلة البحوث المالية والتجارية | ||||
| Article 13, Volume 23, Issue 4 - Serial Number 3, October 2022, Page 360-373 PDF (385 K) | ||||
| Document Type: المقالة الأصلية | ||||
| DOI: 10.21608/jsst.2022.169520.1497 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
maie kamel   1; maie kamel 2; Hanaa Hanaa Abd El-Redeem Salem2; Mona Nazih Abdel Bary Nazih Abdel Bary3
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| 1;gdm hgj[hvm [hlum 'k'h | ||||
| 2كلية التجارة جامعة طنطا | ||||
| 3كلية التجارة جامعة السويس | ||||
| Abstract | ||||
| 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 | ||||
| Keywords | ||||
| Nonlinear Regression; Cubic Model; Johnson Schumacher Model; Exchange Rate | ||||
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