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Nonlinear Regression

Nonlinear fixed- and mixed-effects regression models

In a nonlinear regression model, the response variable does not need to be expressed as a linear combination of model coefficients and predictor variables. You can perform a nonlinear regression with or without the NonLinearModel object or by using the interactive tool nlintool.


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fitnlmFit nonlinear regression model
fevalEvaluate nonlinear regression model prediction
predictPredict response of nonlinear regression model
randomSimulate responses for nonlinear regression model
partialDependenceCompute partial dependence (Since R2020b)
plotPartialDependenceCreate partial dependence plot (PDP) and individual conditional expectation (ICE) plots
plotResidualsPlot residuals of nonlinear regression model
nlinfitNonlinear regression
nlintoolInteractive nonlinear regression
nlparciNonlinear regression parameter confidence intervals
nlpredciNonlinear regression prediction confidence intervals
nlmefitNonlinear mixed-effects estimation
nlmefitsaFit nonlinear mixed-effects model with stochastic EM algorithm
dummyvarCreate dummy variables
hougenHougen-Watson model
statsetCreate statistics options structure
statgetAccess values in statistics options structure


NonLinearModelNonlinear regression model


Nonlinear Models

Mixed Effects