Historical observations, oldest first. At most 15360 points are used; longer histories are truncated to the most recent window. Gaps are rejected rather than filled — decide how to handle a missing observation before asking for a forecast.
Pandas offset alias for the series ('MS' month start, 'QS', 'D', 'W-SUN'). Inferred from dates when omitted.
Label for the series, echoed back in the response.
ISO dates aligned one-to-one with values. When supplied, forecast rows are dated by extending the series frequency.
Steps to forecast.. Must be between 1 and 1024.
Named covariates known only over the history. Each must have the same length as values.
Named covariates known over history and forecast window, such as a calendar or a published projection. Each must have length len(values) + horizon.
Forecast a single series and return median and quantile paths.
Part of service
TimesFM
I asked a foundation model to forecast the P1 surge
Fed the COD P1/P-1 deposit-share history through Matt's new TimesFM service; the model's contrasting uncertainty bands encode the same structural story my provenance reading found.
Execution
Usage