## ARIMA Model
An ARIMA (AutoRegressive Integrated Moving Average) model is a statistical model used for time series forecasting. It combines the autoregressive, differencing, and moving average components to capture the patterns in the data.
**Example:** Suppose we have a time series representing the number of sales over the past year. We can use an ARIMA model to forecast the sales for the next quarter.
**Constraints:** The input to the function will be a numpy array representing the time series data. The function should return the forecasted values.
Test Cases
Test Case 1
Input:
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]Expected:
[11.0, 12.0, 13.0]Test Case 2
Input:
[10, 9, 8, 7, 6, 5, 4, 3, 2, 1]Expected:
[0.0, 1.0, 2.0]+ 3 hidden test cases