statsmodels.tsa.deterministic.TimeTrend¶

class statsmodels.tsa.deterministic.TimeTrend(constant: bool = True, order: int = 0)[source]¶

Constant and time trend determinstic terms

Parameters

constantbool: Flag indicating whether a constant should be included.
orderint: A non-negative int containing the powers to include (1, 2, …, order).

See also

DeterministicProcess
Seasonality
Fourier
CalendarTimeTrend

Examples

>>> from statsmodels.datasets import sunspots
>>> from statsmodels.tsa.deterministic import TimeTrend
>>> data = sunspots.load_pandas().data
>>> trend_gen = TimeTrend(True, 3)
>>> trend_gen.in_sample(data.index)

Attributes

constant: Flag indicating that a constant is included
is_dummy: Flag indicating whether the values produced are dummy variables
order: Order of the time trend

Methods

`from_string`(trend)	Create a TimeTrend from a string description.
`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

Methods

`from_string`(trend)	Create a TimeTrend from a string description.
`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

`constant`	Flag indicating that a constant is included
`is_dummy`	Flag indicating whether the values produced are dummy variables
`order`	Order of the time trend