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Modelos no lineales
Regresión no lineal con múltiples variables predictoras
Clases
NonLinearModel | Nonlinear regression model class |
Funciones
fitnlm | Fit nonlinear regression model |
disp | Display nonlinear regression model |
feval | Evaluate nonlinear regression model prediction |
predict | Predict response of nonlinear regression model |
random | Simulate responses for nonlinear regression model |
dummyvar | Create dummy variables |
hougen | Hougen-Watson model |
plotPartialDependence | Create partial dependence plot (PDP) and individual conditional expectation (ICE) plots |
statset | Create statistics options structure |
statget | Access values in statistics options structure |
Ejemplos y procedimientos
Import data, fit a nonlinear regression, test its quality, modify it to improve the quality, and make predictions based on the model.
Pitfalls in Fitting Nonlinear Models by Transforming to Linearity
This example shows pitfalls that can occur when fitting a nonlinear model by transforming to linearity.
Conceptos
Parametric nonlinear models represent the relationship between a continuous response variable and one or more continuous predictor variables.
