Rolling Standard Deviation Transform

rolling_std_step(
    name: str,
    **kwargs: Any,
) -> MCStep

rolling_std_step computes a trailing rolling standard deviation over the time axis. The output shape is (n - window + 1, k).

Key Parameters:

Name	Default	Description
source	required	Input source channel.
filter_key	`"filter"`	Filter result key when reading filter output.
payload_key	`None`	Producer payload key when `source="payload"`.
columns	`None`	Optional column subset.
burn_in	`0`	Rows dropped before transformation.
drop_initial	`False`	Drop the initial state row for state inputs.
window	`10`	Rolling window length. Must be at least `1` and no longer than the selected input.
ddof	`0`	Standard-deviation degrees-of-freedom correction.

The output is stored in the step payload and can be consumed downstream with source="payload".