NonlinearRegressionModel Class

Represents a nonlinear regression model.

Definition

Namespace: Numerics.NET.Statistics
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.2
C#
public class NonlinearRegressionModel : RegressionModel<double>
Inheritance
Object  →  Model  →  RegressionModel<Double>  →  NonlinearRegressionModel

Remarks

Use the NonlinearRegressionModel class to analyze a nonlinear relationship between two or more numerical variables. A nonlinear regression model tries to express one variable, called the dependent variable, as a function of one or more other variables called independent variables or predictors.

The nonlinear model is specified in the form of a NonlinearCurve.

Constructors

Properties

AdjustedRSquared Gets the adjusted R Squared value for the regression.
(Overrides RegressionModel<T>.AdjustedRSquared)
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>)
Curve Gets or sets the NonlinearCurve that defines the nonlinear model.
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>)
InitialGuess Gets or sets the initial values for the curve parameters.
InputSchema Gets the schema for the features used for fitting the model.
(Inherited from Model)
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)
Method Gets or sets the nonlinear least squares algorithm that is to be used in the calculations.
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)
Optimizer Gets the optimizer used to calculate the nonlinear least-squares solution.
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.
(Inherited from Model)
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 Fits the model to the data.
(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>)
GetHashCodeServes as the default hash function.
(Inherited from Object)
GetTypeGets the Type of the current instance.
(Inherited from Object)
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