The output of which function can serve as input for the rolling average function?

The rolling average function is typically used to smooth out data over a specified period, providing insights into trends by taking the average of a subset of data points within a shifting window. The output of the predict function generates a set of forecasted values based on historical data trends and patterns. These forecasted values can then be fed into the rolling average function to further analyze the trend over time.

The predict function is designed to provide an estimation of future data points, and utilizing these predictions in conjunction with the rolling average allows for a refined understanding of expected future performance by incorporating both historical trends and anticipated outcomes. This is particularly useful in scenarios where understanding future behavior based on previous data is crucial for decision-making.

Other functions listed, such as the standard deviation function, mean absolute percentage deviation, and disaggregation rates function, either provide statistical measures or cause alterations to existing data without generating a value set specifically suitable as input for calculating a rolling average. Hence, only the output from the predict function aligns directly with the input requirements of the rolling average function for subsequent analysis.