The ML.ARIMA_COEFFICIENTS function

ML.ARIMA_COEFFICIENTS function

The ML.ARIMA_COEFFICIENTS function lets you see the ARIMA coefficients. This function only applies to the time-series ARIMA_PLUS and ARIMA models.

For information about model weights support in BigQuery ML, see Model weights overview.

For information about supported model types of each SQL statement and function, and all supported SQL statements and functions for each model type, read End-to-end user journey for each model.

ML.ARIMA_COEFFICIENTS syntax

ML.ARIMA_COEFFICIENTS(MODEL `project_id.dataset.model`)

Where:

  • project_id: your project ID
  • dataset: the BigQuery dataset that contains the model
  • model: the name of the model

ML.ARIMA_COEFFICIENTS output

The ML.ARIMA_COEFFICIENTS function returns the following columns:

  • time_series_id_col or time_series_id_cols: the identifiers of a time series. Only present when forecasting multiple time series at once. The column names and types are inherited from the TIME_SERIES_ID_COL option as specified in the model creation query.
  • ar_coefficients (ARRAY<FLOAT64>): the autoregressive coefficients, which corresponds to non-seasonal p.
  • ma_coefficients (ARRAY<FLOAT64>): the moving-average coefficients, which corresponds to non-seasonal q.
  • intercept_or_drift (FLOAT64): the constant term of the ARIMA model. By definition, the constant term is called “intercept” when non-seasonal d is 0, and “drift” when non-seasonal d is 1. It is always 0 when non-seasonal d is 2.

ML.ARIMA_COEFFICIENTS examples

The following example retrieves the model coefficients information from mymodel in mydataset. The dataset is in your default project.

SELECT
  *
FROM
  ML.ARIMA_COEFFICIENTS(MODEL `mydataset.mymodel`)