Various approaches to producing PIs
PIs are an essential tool in forecasting, allowing practitioners to understand the range within which future observations are likely to fall. Various approaches have been developed to produce these intervals, each with advantages, applications, and challenges. This section will explore the most prominent techniques for creating PIs.
Parametric approaches
Parametric approaches make specific assumptions about the distribution of forecast errors to derive PIs. Some standard techniques in this category are as follows:
- Normal distribution assumptions: By assuming that the forecast errors follow a normal distribution, we can compute symmetric PIs based on standard errors and critical values from the normal distribution.
- Time series models: Models such as ARIMA and exponential smoothing can generate PIs by modeling the underlying stochastic process and using the estimated parameters to produce intervals.
- Generalized linear models ...
