Struct googapis::google::cloud::bigquery::v2::model::arima_forecasting_metrics::ArimaSingleModelForecastingMetrics [−][src]
pub struct ArimaSingleModelForecastingMetrics {
pub non_seasonal_order: Option<ArimaOrder>,
pub arima_fitting_metrics: Option<ArimaFittingMetrics>,
pub has_drift: bool,
pub time_series_id: String,
pub time_series_ids: Vec<String>,
pub seasonal_periods: Vec<i32>,
pub has_holiday_effect: Option<bool>,
pub has_spikes_and_dips: Option<bool>,
pub has_step_changes: Option<bool>,
}
Expand description
Model evaluation metrics for a single ARIMA forecasting model.
Fields
non_seasonal_order: Option<ArimaOrder>
Non-seasonal order.
arima_fitting_metrics: Option<ArimaFittingMetrics>
Arima fitting metrics.
has_drift: bool
Is arima model fitted with drift or not. It is always false when d is not 1.
time_series_id: String
The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
time_series_ids: Vec<String>
The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
seasonal_periods: Vec<i32>
Seasonal periods. Repeated because multiple periods are supported for one time series.
has_holiday_effect: Option<bool>
If true, holiday_effect is a part of time series decomposition result.
has_spikes_and_dips: Option<bool>
If true, spikes_and_dips is a part of time series decomposition result.
has_step_changes: Option<bool>
If true, step_changes is a part of time series decomposition result.
Implementations
pub fn seasonal_periods(
&self
) -> FilterMap<Cloned<Iter<'_, i32>>, fn(_: i32) -> Option<SeasonalPeriodType>>
pub fn seasonal_periods(
&self
) -> FilterMap<Cloned<Iter<'_, i32>>, fn(_: i32) -> Option<SeasonalPeriodType>>
Returns an iterator which yields the valid enum values contained in seasonal_periods
.
Appends the provided enum value to seasonal_periods
.
Trait Implementations
fn merge_field<B>(
&mut self,
tag: u32,
wire_type: WireType,
buf: &mut B,
ctx: DecodeContext
) -> Result<(), DecodeError> where
B: Buf,
Returns the encoded length of the message without a length delimiter.
Encodes the message to a buffer. Read more
Encodes the message to a newly allocated buffer.
Encodes the message with a length-delimiter to a buffer. Read more
Encodes the message with a length-delimiter to a newly allocated buffer.
Decodes an instance of the message from a buffer. Read more
fn decode_length_delimited<B>(buf: B) -> Result<Self, DecodeError> where
Self: Default,
B: Buf,
fn decode_length_delimited<B>(buf: B) -> Result<Self, DecodeError> where
Self: Default,
B: Buf,
Decodes a length-delimited instance of the message from the buffer.
Decodes an instance of the message from a buffer, and merges it into self
. Read more
Decodes a length-delimited instance of the message from buffer, and
merges it into self
. Read more
This method tests for self
and other
values to be equal, and is used
by ==
. Read more
This method tests for !=
.
Auto Trait Implementations
impl Send for ArimaSingleModelForecastingMetrics
impl Sync for ArimaSingleModelForecastingMetrics
impl Unpin for ArimaSingleModelForecastingMetrics
Blanket Implementations
Mutably borrows from an owned value. Read more
Wrap the input message T
in a tonic::Request
pub fn vzip(self) -> V
Attaches the provided Subscriber
to this type, returning a
WithDispatch
wrapper. Read more
Attaches the current default Subscriber
to this type, returning a
WithDispatch
wrapper. Read more