plotSlice

Class: GeneralizedLinearModel

Plot of slices through fitted generalized linear regression surface

Syntax

plotSlice(mdl)
h = plotSlice(mdl)

Description

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.

Tips

  • 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.

Input Arguments

mdl

Generalized linear model, as constructed by fitglm or stepwiseglm.

Output Arguments

h

Vector of handles to lines or patches in the plot.

Examples

expand all

Slice Plot of Generalized Linear Regression Model

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','distr','poisson');

Create the slice plot.

plotSlice(mdl)

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

Was this topic helpful?