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  • ArimaModel Class
  • AugmentedDickeyFullerTest Class
  • DickeyFullerTestType Enumeration
  • ExponentialSmoothingMethod Enumeration
  • ExponentialSmoothingModel Class
  • ExponentialSmoothingTrendEstimator Enumeration
  • GarchInnovationDistribution Enumeration
  • GarchModel Class
  • TimeSeriesCollection Class
  • TimeSeriesFunctions Class
  • TimeSeriesModel Class
• ExponentialSmoothingModel Class
  • ExponentialSmoothingModel Constructors
  • Properties
  • Methods
• Methods
  • ComputeModel Method Overloads
  • Forecast Method Overloads
  • GetAkaikeInformationCriterion Method
  • GetBayesianInformationCriterion Method
  • GetLogLikelihood Method
  • Summarize Method

ExponentialSmoothingModel Methods

Extreme Optimization Numerical Libraries for .NET Professional

The ExponentialSmoothingModel type exposes the following members.

Methods

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	Name	Description
	Compute	Computes the model. (Inherited from Model.)
	Compute(ParallelOptions)	Computes the model. (Inherited from Model.)
	ComputeModel	Computes the model. (Inherited from Model.)
	ComputeModel(ParallelOptions)	Computes the model. (Overrides ModelComputeModel(ParallelOptions).)
	ComputeModel(ModelInput, ParallelOptions)	Computes the model. (Overrides ModelComputeModel(ModelInput, ParallelOptions).)
	Contains	Returns whether another UnivariateModel is nested within this instance. (Inherited from Model.)
	Equals	Determines whether the specified Object is equal to the current Object. (Inherited from Object.)
	Finalize	Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.)
	Fit	Fits the model to the data. (Inherited from Model.)
	Fit(ParallelOptions)	Fits the model to the data. (Inherited from Model.)
	FitCore	Computes the model to the specified input using the specified parallelization options. (Inherited from Model.)
	Forecast	Returns the one step ahead forecast. (Inherited from TimeSeriesModel.)
	Forecast(Int32)	Returns the forecast for the specified number of steps ahead. (Overrides TimeSeriesModelForecast(Int32).)
	GetAkaikeInformationCriterion	Returns an approximation to the Akaike information criterion (AIC) value for the model. (Overrides UnivariateModelGetAkaikeInformationCriterion.)
	GetBayesianInformationCriterion	Returns an approximation to the Bayesian information criterion (AIC) value for the model. (Overrides UnivariateModelGetBayesianInformationCriterion.)
	GetHashCode	Serves as a hash function for a particular type. (Inherited from Object.)
	GetLogLikelihood	Gets an approximation to the log-likelihood of the fitted ARIMA model. (Overrides UnivariateModelGetLogLikelihood.)
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	ResetComputation	Clears all computed model parameters. (Inherited from Model.)
	SetAnovaModelRow	Sets the data of a row in the model's AnovaTable. (Inherited from UnivariateModel.)
	SetAnovaRow	Sets the data of a row in the model's AnovaTable. (Inherited from UnivariateModel.)
	SetDataSource	Uses the specified data frame as the source for all input variables. (Inherited from Model.)
	Summarize	Returns a string containing a human-readable summary of the object using default options. (Inherited from Model.)
	Summarize(SummaryOptions)	Returns a string containing a human-readable summary of the object using the specified options. (Inherited from Model.)
	ToString	Returns a string that represents the current object. (Inherited from Model.)
	ToString	Returns a string that represents the current object. (Inherited from Object.)

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See Also

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Reference

ExponentialSmoothingModel Class

Extreme.Statistics.TimeSeriesAnalysis Namespace

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