Differences - Nixtla

`num_seas_diffs`

num_seas_diffs(x, season_length, max_d=1)

Determine the optimal number of seasonal differences for stationarity. Uses a seasonal strength heuristic based on STL decomposition to determine if seasonal differencing is needed. The function applies seasonal differencing iteratively until the seasonal strength falls below the threshold or the maximum number of differences is reached. Parameters:

Name	Type	Description	Default
`x`	`ndarray`	Array with the time series.	required
`season_length`	`int`	Length of the seasonal pattern.	required
`max_d`	`int`	Maximum number of differences to consider. Defaults to 1.	`1`

Returns:

Name	Type	Description
`int`	`int`	Optimal number of seasonal differences.

`num_diffs`

num_diffs(x, max_d=1)

Determine the optimal number of non-seasonal differences for stationarity. Uses the KPSS (Kwiatkowski-Phillips-Schmidt-Shin) test to determine how many times the series needs to be differenced to achieve stationarity. The function applies differencing iteratively until the KPSS statistic falls below the threshold or the maximum number of differences is reached. Parameters:

Name	Type	Description	Default
`x`	`ndarray`	Array with the time series.	required
`max_d`	`int`	Maximum number of differences to consider. Defaults to 1.	`1`

Returns:

Name	Type	Description
`int`	`int`	Optimal number of differences.

`diff`

diff(x, d)

Subtract previous values of the series Parameters:

Name	Type	Description	Default
`x`	`ndarray`	Array with the time series.	required
`d`	`int`	Lag to subtract	required

Returns:

Type	Description
`ndarray`	np.ndarray: Differenced time series.