Seasonal Naïve

The Seasonal Naïve is a forecasting technique that uses a series temporal's history to predict its future values. It is considered one of the simplest and easiest to implement techniques, but also one of the least precise. However, it can be useful in cases where there are not enough historical data or where the series temporal does not present clear patterns.

The formula used for the Seasonal Naïve is simple: y_{t+1} = y_{t+1−s}, where y_{t+1} is the forecast for the next period and s is the seasonality period. For example, if you are working with a daily series and the seasonality period is 365 days (a year), the formula would be y_{t+1} = y_{t+365}.

The Seasonal Naïve is useful in cases where you need a quick and simple forecast, without the need for complex statistical analysis. For example, in cases of inventory planning or in production management systems, a simple forecast can be enough to make informed decisions.

However, it is essential to remember that the Seasonal Naïve does not take into account external factors that may affect the series temporal, such as changes in trends or non-seasonal events. Therefore, it is essential to be careful when using this technique and consider other factors that may affect the forecast.