I am building my first R project about forecasting rental car sales. I have 2 data sets which have different calculations and consist of daily and monthly data for 10 years.
I want to forecast daily, monthly and quarter-year. I have used time series and auto.arima modeling for observing the trend and seasonality of the datasets. In addition to arima modeling, ı used some feature values such as holidays, weather situations as regressors and gbm (gradient boosting model). but, the results of the prediction is not good enough.
green line: auto.arima forecasting with regressors
blue line: auto.arima forecasting without regressors
red line:. real data
What is the best model to enhance results?