I have the time series of car rentals/demand in a location. The time axis is every hour for 3 months. The y-axis is number of car rentals/demand.
I want to do prediction for future hours given this information. I would like to know the prediction models for this type of data.
I am not sure about the performance of ARIMA or other time series predicion models given low values of car rentals at each hour (close to zero). The maximum is only 5 car rentals.
What are the typical and high accuracy methods? It could be statistical or machine-learning based models.
dpois(0:5,0.8)*720
equals323.5168542 258.8134833 103.5253933 27.6067716 5.5213543 0.8834167
. The fit for predictions of 3/4/5 days are pretty close to your graph I believe by eye. $\endgroup$