deseasonalized
Deseasonalized is an adjective used for a time series or data set from which the seasonal component has been removed, with the aim of revealing underlying non-seasonal patterns such as trend and irregular fluctuations. Deseasonalized data helps analysts compare values across different times of year and assess longer-term movements without predictable seasonal effects.
Removal is typically accomplished through time series decomposition. In an additive model, observations y_t are expressed
Some contexts treat deseasonalized data and seasonally adjusted data as interchangeable, since both involve removing regular
Applications include economics, where monthly or quarterly indicators are deseasonalized to compare performance across months, and