Arima Model 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#
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23
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
Arima | Constructs a new ARMA model. |
Arima | Constructs a new ARIMA model. |
Arima | Constructs a new ARMA model. |
Arima | Constructs a new ARIMA model. |
Properties
Auto | Gets or sets the number of auto-regressive terms in the ARIMA model. |
Auto | Gets the parameters corresponding to the auto-regressive terms in the model. |
Base |
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. |
Covariance |
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) |
Degree | Gets or sets the degree of differencing of the ARIMA model. |
Degrees |
Gets the total degrees of freedom of the data.
(Inherited from TimeSeriesModel<T>) |
Error | Gets the error variance of the time series. |
Estimate | Gets or sets whether the model contains a constant (mean) term. |
Fitted |
Gets whether the model has been computed.
(Inherited from Model) |
Input |
Gets the schema for the features used for fitting the model.
(Inherited from Model) |
Log |
Gets the log-likelihood that the model generated the data.
(Inherited from TimeSeriesModel<T>) |
Max |
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. |
Model |
Gets the collection of variables used in the model.
(Inherited from Model) |
Moving | Gets or sets the number of moving average terms in the ARIMA model. |
Moving | Gets the parameters corresponding to the moving averagw terms in the model. |
Number |
Gets the number of observations the model is based on.
(Inherited from Model) |
Parallel |
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>) |
Parameter |
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>) |
Pseudo | Gets the pseudo R Squared value for the ARIMA model. |
Residuals |
Gets a vector containing the residuals of the model.
(Inherited from TimeSeriesModel<T>) |
Residual |
Gets the sum of squares of the residuals of the model.
(Inherited from TimeSeriesModel<T>) |
Standard |
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) |
Supports |
Indicates whether the model supports case weights.
(Inherited from Model) |
Time |
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( |
Computes the model.
(Inherited from Model) Obsolete. |
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( |
Fits the model to the data.
(Inherited from Model) |
Fit |
Fits the model to the data.
(Overrides Model.FitCore(ModelInput, ParallelOptions)) |
Forecast() |
Returns the one step ahead forecast.
(Inherited from TimeSeriesModel<T>) |
Forecast( |
Returns the forecast for the specified time period.
(Overrides TimeSeriesModel<T>.Forecast(Int32)) |
Get |
Returns the Akaike information criterion (AIC) value for the model.
(Inherited from TimeSeriesModel<T>) |
Get |
Returns the Bayesian information criterion (BIC) value for the model.
(Inherited from TimeSeriesModel<T>) |
Get | Gets the Durbin-Watson statistic for the residuals of the regression. |
GetHashCode | Serves as the default hash function. (Inherited from Object) |
Get | Gets the Ljung-Box test for the residuals of the ARIMA model. |
GetType | Gets the Type of the current instance. (Inherited from Object) |
MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object) |
Reset |
Clears all fitted model parameters.
(Inherited from Model) Obsolete. |
Reset |
Clears all fitted model parameters.
(Inherited from Model) |
Set |
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( |
Returns a string containing a human-readable summary of the object using the specified options.
(Overrides Model.Summarize(SummaryOptions)) |
ToString | Returns a string that represents the current object. (Inherited from Model) |