ArimaModel Class

Represents an AutoRegressive Integrated Moving Average (ARIMA) model.

Definition

Namespace: Extreme.Statistics.TimeSeriesAnalysis
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23
C#
public class ArimaModel : TimeSeriesModel<double>
Inheritance
Object  →  Model  →  TimeSeriesModel<Double>  →  ArimaModel

Remarks

Use the ArimaModel class to represent Auto-Regressive Integrated Moving Average (ARIMA) models using the methodology of Box and Jenkins.

The ArimaModel class can represent pure auto-regressive (AR) models, pure moving average (MA) models, mixed auto-regressive and moving average (ARMA) models, as well as the integrated form of all of these (ARIMA).

Constructors

ArimaModel(Int32, Int32) Constructs a new ARMA model.
ArimaModel(Int32, Int32, Int32) Constructs a new ARIMA model.
ArimaModel(Vector<Double>, Int32, Int32) Constructs a new ARMA model.
ArimaModel(Vector<Double>, Int32, Int32, Int32) Constructs a new ARIMA model.

Properties

AutoRegressiveOrder Gets or sets the number of auto-regressive terms in the ARIMA model.
AutoRegressiveParameters Gets the parameters corresponding to the auto-regressive terms in the model.
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.
(Inherited from TimeSeriesModel<T>)
Data Gets an object that contains all the data used as input to the model.
(Inherited from Model)
DegreeOfDifferencing Gets or sets the degree of differencing of the ARIMA model.
DegreesOfFreedom Gets the total degrees of freedom of the data.
(Inherited from TimeSeriesModel<T>)
ErrorVariance Gets the error variance of the time series.
EstimateMean Gets or sets whether the model contains a constant (mean) term.
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.
(Inherited from TimeSeriesModel<T>)
MaxDegreeOfParallelism Gets or sets the maximum degree of parallelism enabled by this instance.
(Inherited from Model)
Mean Gets or sets the mean of the time series.
ModelSchema Gets the collection of variables used in the model.
(Inherited from Model)
MovingAverageOrder Gets or sets the number of moving average terms in the ARIMA model.
MovingAverageParameters Gets the parameters corresponding to the moving averagw terms in the 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.
(Inherited from TimeSeriesModel<T>)
ParameterValues Gets the collection of parameters associated with this model.
(Inherited from TimeSeriesModel<T>)
Predictions Gets a vector containing the model's predicted values for the dependent variable.
(Inherited from TimeSeriesModel<T>)
PseudoRSquared Gets the pseudo R Squared value for the ARIMA model.
Residuals Gets a vector containing the residuals of the model.
(Inherited from TimeSeriesModel<T>)
ResidualSumOfSquares Gets the sum of squares of the residuals of the model.
(Inherited from TimeSeriesModel<T>)
StandardError Gets the standard error of the regression.
(Inherited from TimeSeriesModel<T>)
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.
(Inherited from TimeSeriesModel<T>)
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 Fits the model to the data.
(Overrides Model.FitCore(ModelInput, ParallelOptions))
Forecast() Returns the one step ahead forecast.
(Inherited from TimeSeriesModel<T>)
Forecast(Int32) Returns the forecast for the specified time period.
(Overrides TimeSeriesModel<T>.Forecast(Int32))
GetAkaikeInformationCriterion Returns the Akaike information criterion (AIC) value for the model.
(Inherited from TimeSeriesModel<T>)
GetBayesianInformationCriterion Returns the Bayesian information criterion (BIC) value for the model.
(Inherited from TimeSeriesModel<T>)
GetDurbinWatsonStatistic Gets the Durbin-Watson statistic for the residuals of the regression.
GetHashCodeServes as the default hash function.
(Inherited from Object)
GetLjungBoxTest Gets the Ljung-Box test for the residuals of the ARIMA model.
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.
(Overrides Model.Summarize(SummaryOptions))
ToStringReturns a string that represents the current object.
(Inherited from Model)

See Also