Nonlinear
Represents a nonlinear regression model.
Definition
Namespace: Extreme.Statistics
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23
C#
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23
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
| Nonlinear | Constructs a new SimpleRegressionModel. |
| Nonlinear | Constructs a new NonlinearRegressionModel. |
| Nonlinear | Constructs a new NonlinearRegressionModel. |
Properties
| Adjusted |
Gets the adjusted R Squared value for the regression.
(Overrides RegressionModel<T>.AdjustedRSquared) |
| Anova |
Gets the AnovaTable that summarizes the results of this model.
(Inherited from RegressionModel<T>) |
| Base |
Gets an index containing the keys of the columns
that are required inputs to the model.
(Inherited from Model) |
| Best |
Gets a vector containing the values of the regression parameters.
Obsolete. |
| Computed |
Gets whether the model has been computed.
(Inherited from Model) Obsolete. |
| Covariance |
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) |
| Degrees |
Gets the total degrees of freedom of the data.
(Inherited from RegressionModel<T>) |
| Dependent |
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>) |
| Independent |
Gets a matrix whose columns contain the independent variables in the model.
(Inherited from RegressionModel<T>) |
| Initial | Gets or sets the initial values for the curve parameters. |
| Input |
Gets the schema for the features used for fitting the model.
(Inherited from Model) |
| Log |
Gets the log-likelihood that the model generated the data.
(Inherited from RegressionModel<T>) |
| Max |
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. |
| Model |
Gets the collection of variables used in the model.
(Inherited from Model) |
| Number |
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. |
| Parallel |
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>) |
| Parameter |
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>) |
| Residual |
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>) |
| Standard |
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) |
| Supports |
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( |
Computes the model.
(Inherited from Model) Obsolete. |
| Contains |
Returns whether another RegressionModel<T> is nested
within this instance.
(Inherited from RegressionModel<T>) |
| Equals | Determines whether the specified object is equal to the current object. (Inherited from Object) |
| Finalize | Allows 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( |
Fits the model to the data.
(Inherited from Model) |
| Fit |
Fits the model to the data.
(Overrides Model.FitCore(ModelInput, ParallelOptions)) |
| Get |
Returns the Akaike information criterion (AIC) value for the model.
(Inherited from RegressionModel<T>) |
| Get |
Returns the Bayesian information criterion (BIC) value for the model.
(Inherited from RegressionModel<T>) |
| GetHashCode | Serves as the default hash function. (Inherited from Object) |
| GetType | Gets the Type of the current instance. (Inherited from Object) |
| MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object) |
| Predict( | Predicts the value of the dependent variable based on the specified value of the independent variable. |
| Predict( |
Predicts the value of the output corresponding to
the specified features.
(Inherited from RegressionModel<T>) |
| Predict( |
Predicts the value of the output corresponding to
the specified features.
(Inherited from RegressionModel<T>) |
| Predict( |
Predicts the value of the output corresponding to
the specified features.
(Inherited from RegressionModel<T>) |
| Predict |
Predicts the value of the dependent variable based on
the specified values of the features.
(Overrides RegressionModel<T>.PredictCore(Matrix<T>, Boolean)) |
| Predict |
Predicts the value of the dependent variable based on
the specified values of the features.
(Overrides RegressionModel<T>.PredictCore(Vector<T>, Boolean)) |
| Reset |
Clears all fitted model parameters.
(Inherited from Model) Obsolete. |
| Reset |
Clears all fitted model parameters.
(Inherited from Model) |
| Set |
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( |
Returns a string containing a human-readable summary of the object using the specified options.
(Inherited from RegressionModel<T>) |
| ToString | Returns a string that represents the current object. (Inherited from Model) |