Plot of slices through fitted generalized linear regression surface


h = plotSlice(mdl)


plotSlice(mdl) creates a new figure containing a series of plots, each representing a slice through the regression surface predicted by mdl. For each plot, the surface slice is shown as a function of a single predictor variable, with the other predictor variables held constant.

h = plotSlice(mdl) returns handles to the lines in the plot.

Input Arguments


Generalized linear model, specified as a full GeneralizedLinearModel object constructed using fitglm or stepwiseglm, or a compacted CompactGeneralizedLinearModel object constructed using compact.

Output Arguments


Vector of handles to lines or patches in the plot.


expand all

Create a slice plot of a Poisson generalized linear model.

Generate artificial data for the model using Poisson random numbers with two underlying predictors X(1) and X(2).

rng('default') % for reproducibility
rndvars = randn(100,2);
X = [2+rndvars(:,1),rndvars(:,2)];
mu = exp(1 + X*[1;2]);
y = poissrnd(mu);

Create a generalized linear regression model of Poisson data.

mdl = fitglm(X,y,'y ~ x1 + x2','Distribution','poisson');

Create the slice plot.


Drag the x1 prediction line to the right and view the changes in the prediction and the response curve for the x2 predictor.


  • If there are more than eight predictors, plotSlice selects the first five for plotting. Use the Predictors menu to control which predictors are plotted.

  • The Bounds menu lets you choose between simultaneous or non-simultaneous bounds, and between bounds on the function or bounds on a new observation.