SimpleRegressionModel Class

Represents a linear regression model.

Definition

Namespace: Numerics.NET.Statistics
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.4
C#
public class SimpleRegressionModel : RegressionModel<double>
Inheritance
Object  →  Model  →  RegressionModel<Double>  →  SimpleRegressionModel

Remarks

Use the SimpleRegressionModel class to investigate a linear relationship between two variables. The technique used to model such a relationship is called simple linear regression.

SimpleRegressionModel inherits from LinearRegressionModel, but has special constructors that make it easier to create simple regression models. It also defines some members that may be more appropriate for the simple case. For example, the GetRegressionLine() method returns a Polynomial object that represents the resulting regression line.

By setting the Kind property, it is possible to compute linearized versions of non-linear regression functions. When a kind other than linear regression is chosen, a linearization transformation is applied to one or both of the variables before the regression line is computed. The residuals are those of the transformed regression model. The parameter values are transformed back if needed.

Constructors

Properties

AdjustedRSquared Gets the adjusted R Squared value for the regression.
(Inherited from RegressionModel<T>)
AnovaTable Gets the AnovaTable that summarizes the results of this model.
(Inherited from RegressionModel<T>)
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 RegressionModel<T>)
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.
(Inherited from RegressionModel<T>)
DependentVariable Gets a vector that contains the dependent variable that is to be fitted.
(Inherited from RegressionModel<T>)
Fitted Gets whether the model has been computed.
(Inherited from Model)
FStatistic Gets the F statistic for the regression.
(Inherited from RegressionModel<T>)
IndependentVariables Gets a matrix whose columns contain the independent variables in the model.
(Inherited from RegressionModel<T>)
InputSchema Gets the schema for the features used for fitting the model.
(Inherited from Model)
Kind Gets or sets the kind of linearized regression to perform.
LogLikelihood Gets the log-likelihood that the model generated the data.
(Inherited from RegressionModel<T>)
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)
NoIntercept Gets or sets whether to include the intercept or constant term in the regression 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 RegressionModel<T>)
ParameterValues Gets the values of the parameters associated with this model.
(Inherited from RegressionModel<T>)
Predictions Gets a vector containing the model's predicted values for the dependent variable.
(Inherited from RegressionModel<T>)
PValue Gets the probability corresponding to the F statistic for the regression.
(Inherited from RegressionModel<T>)
Residuals Gets a vector containing the residuals of the model.
(Inherited from RegressionModel<T>)
ResidualSumOfSquares Gets the sum of squares of the residuals of the model.
(Inherited from RegressionModel<T>)
RSquared Gets the R Squared value for the regression.
(Inherited from RegressionModel<T>)
StandardError Gets the standard error of the regression.
(Inherited from RegressionModel<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.
(Overrides Model.SupportsWeights)
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.
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>)
GetConfidenceInterval(Double) Gets the 95% confidence interval around the best-fit curve at the specified point.
GetConfidenceInterval(Double, Double) Gets the confidence interval around the best-fit curve at the specified point.
GetDurbinWatsonStatistic Gets the Durbin-Watson statistic for the residuals of the regression.
GetHashCodeServes as the default hash function.
(Inherited from Object)
GetPredictionInterval(Double) Gets the prediction interval around the best-fit curve at the specified point.
GetPredictionInterval(Double, Double) Gets the width of the prediction band around the best-fit curve at the specified point.
GetRegressionCurve Returns the regression curve.
GetRegressionLine Returns the regression line.
GetTypeGets the Type of the current instance.
(Inherited from Object)
GetWorkingHotellingConfidenceBandwidth(Vector<Double>) Gets the width of the 95% Working-Hotelling confidence band around the best-fit curve at the specified point.
GetWorkingHotellingConfidenceBandwidth(Vector<Double>, Double) Gets the width of the Working-Hotelling confidence band around the best-fit curve at the specified point.
MemberwiseCloneCreates a shallow copy of the current Object.
(Inherited from Object)
Predict(Double) Predicts the value of the dependent variable based on the specified value of the independent variable.
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<Double>, Boolean) Predicts the value of the dependent variable based on the specified values of the features.
(Overrides RegressionModel<T>.PredictCore(Matrix<T>, Boolean))
PredictCore(Vector<Double>, Boolean) Predicts the value of the dependent variable based on the specified values of the features.
(Overrides RegressionModel<T>.PredictCore(Vector<T>, Boolean))
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