feval - Evaluate nonlinear regression model prediction - MATLAB (original) (raw)

Evaluate nonlinear regression model prediction

Syntax

Description

[ypred](#btbowky%5Fsep%5Fshared-ypred) = feval([mdl](#btbowky%5Fsep%5Fshared-mdl),[Xnew1,Xnew2,...,Xnewn](#btbowky%5Fsep%5Fshared-Xnew1Xnew2Xnewn)) returns the predicted response of mdl to the input[Xnew1,Xnew2,...,Xnewn].

example

Examples

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Create a nonlinear model for auto mileage based on the carbig data. Predict the mileage of an average car.

Load the data and create a nonlinear model.

load carbig tbl = table(Horsepower,Weight,MPG); modelfun = @(b,x)b(1) + b(2)*x(:,1).^b(3) + ... b(4)*x(:,2).^b(5); beta0 = [-50 500 -1 500 -1]; mdl = fitnlm(tbl,modelfun,beta0);

Find the predicted mileage of an average car. The data contains some missing (NaN) observations, so compute the mean using mean with the 'omitnan' option.

Xnew = mean([Horsepower Weight],'omitnan'); MPGnew = feval(mdl,Xnew)

Input Arguments

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Data Types: single | double | table

Output Arguments

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Predicted response values at Xnew1,Xnew2,...,Xnewn, returned as a numeric vector.

Alternatives

predict gives the same predictions, but uses a single input array with one observation in each row, rather than one component in each input argument. predict also gives confidence intervals on its predictions.

random predicts with added noise.

Version History

Introduced in R2012a