PiecewiseLinearTrend

effects.PiecewiseLinearTrend(
    self,
    changepoint_interval=25,
    changepoint_range=0.8,
    changepoint_prior_scale=0.001,
    offset_prior_scale=0.1,
    squeeze_if_single_series=True,
    remove_seasonality_before_suggesting_initial_vals=True,
    global_rate_prior_loc=None,
    offset_prior_loc=None,
)

Piecewise Linear Trend model.

This model assumes that the trend is piecewise linear, with changepoints at regular intervals. The number of changepoints is determined by the changepoint_interval and changepoint_range parameters. The changepoint_interval parameter specifies the interval between changepoints, while the changepoint_range parameter specifies the range of the changepoints.

This implementation is based on the Prophet_ library. The initial values (global rate and global offset) are suggested using the maximum and minimum values of the time series data.

Parameters

Name	Type	Description	Default
changepoint_interval	int	The interval between changepoints.	`25`
changepoint_range	int	The range of the changepoints.	`0.8`
changepoint_prior_scale	dist.Distribution	The prior scale for the changepoints.	`0.001`
offset_prior_scale	float	The prior scale for the offset. Default is 0.1.	`0.1`
squeeze_if_single_series	bool	If True, squeeze the output if there is only one series. Default is True.	`True`
remove_seasonality_before_suggesting_initial_vals	bool	If True, remove seasonality before suggesting initial values, using sktime’s detrender. Default is True.	`True`
global_rate_prior_loc	float	The prior location for the global rate. Default is suggested empirically from data.	`None`
offset_prior_loc	float	The prior location for the offset. Default is suggested empirically from data.	`None`

Attributes

Name	Description
n_changepoint_per_series	Get the number of changepoints per series.
n_changepoints	Get the total number of changepoints.

Methods

Name	Description
get_changepoint_matrix	Return the changepoint matrix for the given index.

get_changepoint_matrix

effects.PiecewiseLinearTrend.get_changepoint_matrix(idx)

Return the changepoint matrix for the given index.

Parameters

Name	Type	Description	Default
idx	pd.PeriodIndex	The index for which to compute the changepoint matrix.	required

Returns

Name	Type	Description
	jnp.ndarray: The changepoint matrix.