LinearRegressionModel Methods

Methods

Compute() Computes the model.
(Inherited from Model)
Obsolete.
Compute(ParallelOptions) Computes the model.
(Inherited from Model)
Obsolete.
Contains Returns whether another RegressionModel<T> is nested within this instance.
(Inherited from RegressionModel<T>)
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.
(Overrides Model.FitCore(ModelInput, ParallelOptions))
GetAkaikeInformationCriterion Returns the Akaike information criterion (AIC) value for the model.
(Inherited from RegressionModel<T>)
GetBayesianInformationCriterion Returns the Bayesian information criterion (BIC) value for the model.
(Inherited from RegressionModel<T>)
GetBreuschGodfreyTest Gets the Breusch-Godfrey test for serial correlation in the residuals of the regression model.
GetConfidenceBandwidth(Vector<Double>) Gets the width of the 95% confidence band around the best-fit curve at the specified point.
GetConfidenceBandwidth(Vector<Double>, Double) Gets the width of the confidence band around the best-fit curve at the specified point.
GetCooksDistance Returns Cook's distance for each of the observations.
GetDeletedResiduals Returns the deleted residual for each observation
GetDffits Returns the DFFITS value for each of the observations.
GetDurbinWatsonStatistic Gets the Durbin-Watson statistic for the residuals of the regression.
GetExternallyStudentizedResiduals Returns the externally studentized residual for each observation.
GetHashCodeServes as the default hash function.
(Inherited from Object)
GetNormalityOfResidualsTest() Returns a test to verify that the residuals follow a normal distribution.
GetNormalityOfResidualsTest(TestOfNormality) Returns a test to verify that the residuals follow a normal distribution.
GetPredictionBandwidth(Vector<Double>) Gets the width of the prediction band around the best-fit curve at the specified point.
GetPredictionBandwidth(Vector<Double>, Double) Gets the width of the prediction band around the best-fit curve at the specified point.
GetStudentizedDeletedResiduals Returns the studentized deleted residual for each observation
GetStudentizedResiduals Returns the studentized residual for each observation.
GetTypeGets the Type of the current instance.
(Inherited from Object)
MemberwiseCloneCreates a shallow copy of the current Object.
(Inherited from Object)
Predict(IDataFrame, ModelInputFormat) Predicts the value of the output corresponding to the specified features.
(Inherited from RegressionModel<T>)
Predict(Matrix<T>, ModelInputFormat) Predicts the value of the output corresponding to the specified features.
(Inherited from RegressionModel<T>)
Predict(Vector<T>, ModelInputFormat) Predicts the value of the output corresponding to the specified features.
(Inherited from RegressionModel<T>)
PredictCore(Matrix<T>, Boolean) Predicts the value of the dependent variable based on the specified values of the features.
(Inherited from RegressionModel<T>)
PredictCore(Vector<T>, Boolean) Predicts the value of the dependent variable based on the specified values of the features.
(Inherited from RegressionModel<T>)
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 RegressionModel<T>)
ToStringReturns a string that represents the current object.
(Inherited from Model)

See Also