, including smooth transition regression models, logistic smooth transition regressions models, threshold autoregressive models … relationships with the US dollar are captured best by neural net regression models, over the ten year sample of daily exchange rate …

regression trees, bagging, random forest, boosting machines and neural networks. Finally, we provide methodologies for analysing …

relationships between their observations. For this purpose, we use a specific type of regression model on an augmented dataset of … lagged time series. Our model is inspired by dynamic regression models (Pankratz 2012), with the response variable’s lags … been successfully applied in the past, to solving regression and classification problems. The novelty of our approach is to …

forest and logistic regression models were the most cited, and thus the models were chosen for this work. Quantitative …

Moroccan economic context over two years. To achieve these objectives, logistic regression and neural networks are used based … regression models obtained by stepwise selection outperform the other models with an overall accuracy of 93.33% two years before …