The AutoARIMA type exposes the following members.
Constructors
Name | Description | |
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AutoARIMA |
Constructor for AutoARIMA.
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Methods
Name | Description | |
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Compute | Overloaded. | |
Equals | (Inherited from Object.) | |
Finalize |
Allows an Object to attempt to free resources and perform other cleanup operations before the Object is reclaimed by garbage collection.
(Inherited from Object.) | |
Forecast |
Computes forecasts, associated probability limits and
weights for the given outlier contaminated time series.
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GetAR |
Returns the final autoregressive parameter estimates of the optimum
model.
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GetCompleteTimes |
Returns all time points at which the original series was observed,
including values for times with missing values in x.
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GetCompleteTimeSeries |
Returns the original series with potentially missing values replaced
by estimates.
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GetDeviations |
Returns the deviations used for calculating the forecast confidence
limits.
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GetForecast |
Returns forecasts for the original outlier contaminated series.
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GetHashCode |
Serves as a hash function for a particular type.
(Inherited from Object.) | |
GetMA |
Returns the final moving average parameter estimates of the optimum
model.
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GetOptimumModelOrder |
Returns the order of the
optimum model.
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GetOutlierFreeForecast |
Returns forecasts for the outlier free series.
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GetOutlierFreeSeries |
Returns the outlier free series.
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GetOutlierStatistics |
Returns the outlier statistics.
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GetPsiWeights |
Returns the weights of the infinite order
moving average form of the model.
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GetResiduals |
Returns the residuals.
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GetType |
Gets the Type of the current instance.
(Inherited from Object.) | |
MemberwiseClone |
Creates a shallow copy of the current Object.
(Inherited from Object.) | |
SetDifferenceOrders |
Defines the orders of the periodic differences used in the determination
of the optimum model.
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SetPeriods |
Defines the periods used in the determination of the optimum model.
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ToString | (Inherited from Object.) |
Fields
Name | Description | |
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ADDITIVE |
Indicates detection of an additive outlier.
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INNOVATIONAL |
Indicates detection of an innovational outlier.
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LEVEL_SHIFT |
Indicates detection of a level shift outlier.
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TEMPORARY_CHANGE |
Indicates detection of a temporary change outlier.
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UNABLE_TO_IDENTIFY |
Indicates detection of an outlier that cannnot be categorized.
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Properties
Name | Description | |
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AccuracyTolerance |
The tolerance value controlling the accuracy of the parameter
estimates.
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AIC |
Akaike's information criterion (AIC) for the optimum model.
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AICC |
Akaike's Corrected Information Criterion (AICC) for the optimum
model.
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BIC |
The Bayesian Information Criterion (BIC) for the optimum model.
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Confidence |
The confidence level used in the calculation of confidence limit
deviations via method GetDeviations.
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Constant |
The constant parameter estimate for the optimum model.
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CriticalValue |
The critical value used as a threshold during outlier detection.
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Delta |
The dampening effect parameter.
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MaximumARLag |
The maximum AR lag used in the determination of the optimum (s,d)
combination of method Compute(int[] arOrders, int[] maOrders).
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ModelSelectionCriterion |
The model selection criterion used in the optimum model search.
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NumberOfOutliers |
The number of detected outliers.
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RelativeError |
The stopping criterion for use in the nonlinear equation solver.
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ResidualStandardError |
The residual standard error of the outlier free series.
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