statsmodels.tsa.deterministic.Seasonality¶

class statsmodels.tsa.deterministic.Seasonality(period, initial_period=1)[source]¶

Seasonal dummy deterministic terms

Parameters:

periodint: The length of a full cycle. Must be >= 2.
initial_periodint: The seasonal index of the first observation. 1-indexed so must be in {1, 2, …, period}.

See also

DeterministicProcess
TimeTrend
Fourier
CalendarSeasonality

Examples

Solar data has an 11-year cycle

>>> from statsmodels.datasets import sunspots
>>> from statsmodels.tsa.deterministic import Seasonality
>>> data = sunspots.load_pandas().data
>>> seas_gen = Seasonality(11)
>>> seas_gen.in_sample(data.index)

To start at a season other than 1

>>> seas_gen = Seasonality(11, initial_period=4)
>>> seas_gen.in_sample(data.index)

Attributes:

initial_period: The seasonal index of the first observation
is_dummy: Flag indicating whether the values produced are dummy variables
period: The period of the seasonality

Methods

`from_index`(index)	Construct a seasonality directly from an index using its frequency.
`in_sample`(index)	Produce deterministic trends for in-sample fitting.
`out_of_sample`(steps, index[, forecast_index])	Produce deterministic trends for out-of-sample forecasts

Properties

`initial_period`	The seasonal index of the first observation
`is_dummy`	Flag indicating whether the values produced are dummy variables
`period`	The period of the seasonality