Represents a statistical model.
SystemObject Extreme.DataAnalysis.ModelsModel Extreme.DataAnalysis.ModelsRegressionModelT Extreme.StatisticsGeneralizedLinearModel Extreme.StatisticsLinearRegressionModel Extreme.StatisticsNonlinearRegressionModel Extreme.StatisticsRegularizedRegressionModel Extreme.StatisticsSimpleRegressionModel
Namespace:
Extreme.DataAnalysis.Models
Assembly:
Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.1
public abstract class RegressionModel<T> : Model
Public MustInherit Class RegressionModel(Of T)
Inherits Model
generic<typename T>
public ref class RegressionModel abstract : public Model
[<AbstractClassAttribute>]
type RegressionModel<'T> =
class
inherit Model
end
Type Parameters
 T
The RegressionModelT type exposes the following members.
 Name  Description 

 RegressionModelT 
Constructs a new univariate model based on a model specification.

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 Name  Description 

 AdjustedRSquared 
Gets the adjusted R Squared value for the regression.

 AnovaTable 
Gets the AnovaTable that summarizes the results of this model.

 BaseFeatureIndex 
Gets an index containing the keys of the columns
that are required inputs to the model.
(Inherited from Model.) 
 Computed  Obsolete.
Gets whether the model has been computed.
(Inherited from Model.) 
 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.

 DependentVariable 
Gets a vector that contains the dependent variable that is to be fitted.

 Fitted 
Gets whether the model has been computed.
(Inherited from Model.) 
 FStatistic 
Gets the F statistic for the regression.

 IndependentVariables 
Gets a matrix whose columns contain the independent variables in the model.

 InputSchema 
Gets the schema for the features used for fitting the model.
(Inherited from Model.) 
 LogLikelihood 
Gets the loglikelihood 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 values of the parameters associated with this model.

 Predictions 
Gets a vector containing the model's predicted values for the dependent variable.

 PValue 
Gets the probability corresponding to the F statistic for the regression.

 Residuals 
Gets a vector containing the residuals of the model.

 ResidualSumOfSquares 
Gets the sum of squares of the residuals of the model.

 RSquared 
Gets the R Squared value for the regression.

 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.) 
 Weights 
Gets or sets the actual weights.
(Inherited from Model.) 
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This is an abstract base class and cannot be instantiated directly. Instead, use one of the
inherited types, as listed in the table below:
Note to inheritors: When you inherit from
RegressionModelT,you must override
FitCore(ModelInput, ParallelOptions).
Reference