Lagged Predictors in Regression Models and Improving by Bootstrapping and Bagging

Huge lines at gas stations have been seen around Turkey in recent days. Under the reason for this is the rise in the prices so often, in the last few months and the expectation to continue this. Of course, it is known that the rise in the exchange rate (US dollar to Turkish lira) hasContinue reading “Lagged Predictors in Regression Models and Improving by Bootstrapping and Bagging”

Dynamic Regression with ARIMA Errors: The Students on the Streets

The higher education students have had trouble being housing in Turkey in recent days. There have been people who even sleep on the streets like a homeless. The government has been accused of investing inadequate dormitories for sheltering the students. Let’s examine the ongoing sheltering problem of students. The dataset we have built for thisContinue reading “Dynamic Regression with ARIMA Errors: The Students on the Streets”

Dynamic Regression (ARIMA) vs. XGBoost

In the previous article, we mentioned that we were going to compare dynamic regression with ARIMA errors and the xgboost. Before doing that, let’s talk about dynamic regression. Time series modeling, most of the time, uses past observations as predictor variables. But sometimes, we need external variables that affect the target variables. To include thoseContinue reading “Dynamic Regression (ARIMA) vs. XGBoost”