ML.ARIMA_COEFFICIENTS function lets you see the ARIMA coefficients.
This function only applies to the time-series
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.
project_id: your project ID
dataset: the BigQuery dataset that contains the model
model: the name of the model
ML.ARIMA_COEFFICIENTS function returns the following columns:
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_COLoption as specified in the model creation query.
ARRAY<FLOAT64>): the autoregressive coefficients, which corresponds to non-seasonal p.
ARRAY<FLOAT64>): the moving-average coefficients, which corresponds to non-seasonal q.
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.
The following example retrieves the model coefficients information from
mydataset. The dataset is in your default project.
SELECT * FROM ML.ARIMA_COEFFICIENTS(MODEL `mydataset.mymodel`)