Class: Google::Apis::BigqueryV2::ArimaSingleModelForecastingMetrics

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/bigquery_v2/classes.rb,
lib/google/apis/bigquery_v2/representations.rb,
lib/google/apis/bigquery_v2/representations.rb

Overview

Model evaluation metrics for a single ARIMA forecasting model.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ ArimaSingleModelForecastingMetrics

Returns a new instance of ArimaSingleModelForecastingMetrics.



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# File 'lib/google/apis/bigquery_v2/classes.rb', line 493

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#arima_fitting_metrics ⇒ Google::Apis::BigqueryV2::ArimaFittingMetrics

ARIMA model fitting metrics. Corresponds to the JSON property arimaFittingMetrics

Returns:



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# File 'lib/google/apis/bigquery_v2/classes.rb', line 440

def arima_fitting_metrics
  @arima_fitting_metrics
end

#has_drift ⇒ Boolean Also known as: has_drift?

Is arima model fitted with drift or not. It is always false when d is not 1. Corresponds to the JSON property hasDrift

Returns:

  • (Boolean) 


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# File 'lib/google/apis/bigquery_v2/classes.rb', line 445

def has_drift
  @has_drift
end

#has_holiday_effect ⇒ Boolean Also known as: has_holiday_effect?

If true, holiday_effect is a part of time series decomposition result. Corresponds to the JSON property hasHolidayEffect

Returns:

  • (Boolean) 


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# File 'lib/google/apis/bigquery_v2/classes.rb', line 451

def has_holiday_effect
  @has_holiday_effect
end

#has_spikes_and_dips ⇒ Boolean Also known as: has_spikes_and_dips?

If true, spikes_and_dips is a part of time series decomposition result. Corresponds to the JSON property hasSpikesAndDips

Returns:

  • (Boolean) 


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# File 'lib/google/apis/bigquery_v2/classes.rb', line 457

def has_spikes_and_dips
  @has_spikes_and_dips
end

#has_step_changes ⇒ Boolean Also known as: has_step_changes?

If true, step_changes is a part of time series decomposition result. Corresponds to the JSON property hasStepChanges

Returns:

  • (Boolean) 


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# File 'lib/google/apis/bigquery_v2/classes.rb', line 463

def has_step_changes
  @has_step_changes
end

#non_seasonal_order ⇒ Google::Apis::BigqueryV2::ArimaOrder

Arima order, can be used for both non-seasonal and seasonal parts. Corresponds to the JSON property nonSeasonalOrder

Returns:



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# File 'lib/google/apis/bigquery_v2/classes.rb', line 469

def non_seasonal_order
  @non_seasonal_order
end

#seasonal_periods ⇒ Array<String>

Seasonal periods. Repeated because multiple periods are supported for one time series. Corresponds to the JSON property seasonalPeriods

Returns:

  • (Array<String>) 


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# File 'lib/google/apis/bigquery_v2/classes.rb', line 475

def seasonal_periods
  @seasonal_periods
end

#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. Corresponds to the JSON property timeSeriesId

Returns:

  • (String) 


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# File 'lib/google/apis/bigquery_v2/classes.rb', line 482

def time_series_id
  @time_series_id
end

#time_series_ids ⇒ Array<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. Corresponds to the JSON property timeSeriesIds

Returns:

  • (Array<String>) 


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# File 'lib/google/apis/bigquery_v2/classes.rb', line 491

def time_series_ids
  @time_series_ids
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



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# File 'lib/google/apis/bigquery_v2/classes.rb', line 498

def update!(**args)
  @arima_fitting_metrics = args[:arima_fitting_metrics] if args.key?(:arima_fitting_metrics)
  @has_drift = args[:has_drift] if args.key?(:has_drift)
  @has_holiday_effect = args[:has_holiday_effect] if args.key?(:has_holiday_effect)
  @has_spikes_and_dips = args[:has_spikes_and_dips] if args.key?(:has_spikes_and_dips)
  @has_step_changes = args[:has_step_changes] if args.key?(:has_step_changes)
  @non_seasonal_order = args[:non_seasonal_order] if args.key?(:non_seasonal_order)
  @seasonal_periods = args[:seasonal_periods] if args.key?(:seasonal_periods)
  @time_series_id = args[:time_series_id] if args.key?(:time_series_id)
  @time_series_ids = args[:time_series_ids] if args.key?(:time_series_ids)
end