Nichtlineare Regression
Nichtlineare Regressionsmodelle mit festen und gemischten Effekten
Bei einem nichtlinearen Regressionsmodell muss die Antwortvariable nicht als lineare Kombination aus Modellkoeffizienten und Prädiktorvariablen ausgedrückt werden. Sie können eine nichtlineare Regression mit oder ohne NonLinearModel-Objekt oder mithilfe des interaktiven Tools Nonlinear Regression Fitter Tool durchführen.
Funktionen
Objekte
NonLinearModel | Nonlinear regression model |
Themen
Nichtlineare Modelle
- Nonlinear Regression
Parametric nonlinear models represent the relationship between a continuous response variable and one or more continuous predictor variables. - Nonlinear Regression Workflow
Import data, fit a nonlinear regression, test its quality, modify it to improve the quality, and make predictions based on the model. - Weighted Nonlinear Regression
This example shows how to fit a nonlinear regression model for data with nonconstant error variance. - 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. - Nonlinear Logistic Regression
This example shows two ways of fitting a nonlinear logistic regression model.
Gemischte Effekte
- Mixed-Effects Models
Mixed-effects models account for both fixed effects (which represent population parameters, assumed to be the same each time data is collected) and random effects (which act like additional error terms). - Mixed-Effects Models Using nlmefit and nlmefitsa
Fit a mixed-effects model, plot predictions and residuals, and interpret the results. - Examining Residuals for Model Verification
Examine thestatsstructure, which is returned by bothnlmefitandnlmefitsa, to determine the quality of your model.
