TimeSeriesModel<T> Class

Represents a time-series model.

Definition

Namespace: Extreme.Statistics.TimeSeriesAnalysis
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23
C#
public abstract class TimeSeriesModel<T> : Model
where T : Object, IComparable<T>
Inheritance
Object  →  Model  →  TimeSeriesModel<T>
Derived

Type Parameters

T

Remarks

Use the TimeSeriesModel<T> class as the base class for implementing time series models. This is an abstract base class and cannot be instantiated directly. Instead, use one of the inherited types, as listed in the table below:

ClassDescription
ExponentialSmoothingModelSingle or double exponential smoothing.
ArimaModelAuto-regressive integrated moving average models.

Constructors

TimeSeriesModel<T> Called by derived classes to constructs a new TimeSeriesModel<T>.

Properties

BaseFeatureIndex Gets an index containing the keys of the columns that are required inputs to the model.
(Inherited from Model)
Computed Gets whether the model has been computed.
(Inherited from Model)
Obsolete.
CovarianceMatrix Gets the covariance matrix of the model parameters.
Data Gets an object that contains all the data used as input to the model.
(Inherited from Model)
DegreesOfFreedom Gets the total degrees of freedom of the data.
Fitted Gets whether the model has been computed.
(Inherited from Model)
InputSchema Gets the schema for the features used for fitting the model.
(Inherited from Model)
LogLikelihood Gets the log-likelihood that the model generated the data.
MaxDegreeOfParallelism Gets or sets the maximum degree of parallelism enabled by this instance.
(Inherited from Model)
ModelSchema Gets the collection of variables used in the model.
(Inherited from Model)
NumberOfObservations Gets the number of observations the model is based on.
(Inherited from Model)
ParallelOptions Gets or sets an object that specifies how the calculation of the model should be parallelized.
(Inherited from Model)
Parameters Gets the collection of parameters associated with this model.
ParameterValues Gets the collection of parameters associated with this model.
Predictions Gets a vector containing the model's predicted values for the dependent variable.
Residuals Gets a vector containing the residuals of the model.
ResidualSumOfSquares Gets the sum of squares of the residuals of the model.
StandardError Gets the standard error of the regression.
Status Gets the status of the model, which determines which information is available.
(Inherited from Model)
SupportsWeights Indicates whether the model supports case weights.
(Inherited from Model)
TimeSeries Gets the time series that is being modeled.
Weights Gets or sets the actual weights.
(Inherited from Model)

Methods

Compute() Computes the model.
(Inherited from Model)
Obsolete.
Compute(ParallelOptions) Computes the model.
(Inherited from Model)
Obsolete.
EqualsDetermines whether the specified object is equal to the current object.
(Inherited from Object)
FinalizeAllows 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.
Forecast(Int32) Returns the forecast for the specified number of steps ahead.
GetAkaikeInformationCriterion Returns the Akaike information criterion (AIC) value for the model.
GetBayesianInformationCriterion Returns the Bayesian information criterion (BIC) value for the model.
GetHashCodeServes as the default hash function.
(Inherited from Object)
GetTypeGets the Type of the current instance.
(Inherited from Object)
MemberwiseCloneCreates a shallow copy of the current Object.
(Inherited from Object)
ResetComputation Clears all fitted model parameters.
(Inherited from Model)
Obsolete.
ResetFit Clears all fitted model parameters.
(Inherited from Model)
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)
ToStringReturns a string that represents the current object.
(Inherited from Model)

See Also