feval

Predict responses of linear regression model using one input for each predictor

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Syntax

ypred = feval(mdl,Xnew1,Xnew2,...,Xnewn)

Description

ypred = feval(mdl,Xnew1,Xnew2,...,Xnewn) returns the predicted response of mdl to the new input predictors Xnew1,Xnew2,...,Xnewn.

example

Examples

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Open Live Script

Fit a mileage model to the carsmall data set, including the Year categorical predictor. Superimpose fitted curves on a scatter plot of the data.

Load the data set and fit the model. 

load carsmall
tbl = table(MPG,Weight);
tbl.Year = categorical(Model_Year);
mdl = fitlm(tbl,'MPG ~ Year + Weight^2');

Create a scatter plot of MPG versus Weight, grouped by Year. 

gscatter(tbl.Weight,tbl.MPG,tbl.Year,'rgb');

Figure contains an axes object. The axes object contains 3 objects of type line. One or more of the lines displays its values using only markers These objects represent 70, 76, 82.

Plot curves of the model predictions for the various years and weights by using feval.

w = linspace(min(tbl.Weight),max(tbl.Weight))';
line(w,feval(mdl,w,'70'),'Color','r')
line(w,feval(mdl,w,'76'),'Color','g')
line(w,feval(mdl,w,'82'),'Color','b')

Figure contains an axes object. The axes object contains 6 objects of type line. One or more of the lines displays its values using only markers These objects represent 70, 76, 82.

Input Arguments

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Linear regression model object, specified as a LinearModel object created by using fitlm or stepwiselm, or a CompactLinearModel object created by using compact.

New input predictor values, specified as a vector, matrix, or table.

  • If you pass multiple inputs Xnew1,Xnew2,...,Xnewn and each includes observations for one predictor variable, then each input must be a vector. Each vector must have the same size. If you specify a predictor variable as a scalar, then feval expands the scalar argument into a constant vector of the same size as the other arguments.

  • If you pass a single input Xnew1, then Xnew1 must be a matrix or table.

    • If Xnew1 is a matrix, it must have the same number of variables (columns) in the same order as the predictor input used to create mdl. Note that Xnew1 must also contain any predictor variables that are as predictors in the fitted model. All variables used in to create mdl must be numeric. To treat numerical predictors as categorical, specify the predictors using the CategoricalVars name-value argument of fitlmcens.

    • If Xnew1 is a table, it must contain predictors that have the same names as predictors in the PredictorNames property of mdl.

Data Types: single | double | table

Output Arguments

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

Tips

  • A regression object is, mathematically, a function that estimates the relationship between the response and predictors. The feval function enables an object to behave like a function in MATLAB®. You can pass feval to another function that accepts a function input, such as fminsearch and integral.

  • feval can be simpler to use with a model created from a table or dataset array. When you have new predictor data, you can pass it to feval without creating a table or matrix.

Alternative Functionality

  • predict gives the same predictions as feval by using a single input argument containing all predictor variables, rather than multiple input arguments with one input for each predictor variable. predict also gives confidence intervals on its predictions.

  • random predicts responses with added noise.

Extended Capabilities

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Version History

Introduced in R2012a

See Also

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