Adjusted response plot for linear regression model
h = plotAdjustedResponse(mdl,var)
h = plotAdjustedResponse(mdl,var,Name,Value)
For many plots, the Data Cursor tool in the figure window displays the x and y values for any data point, along with the observation name or number.
Variable name, or scalar index of variable in mdl.CoefficientNames.
Specify optional comma-separated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside single quotes (' '). You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.
Width of the line or edges of filled area, in points, a positive scalar. One point is 1/72 inch.
Size of the marker in points, a strictly positive scalar. One point is 1/72 inch.
The adjusted response plot shows the fitted response as a function of var, with the other predictors averaged out by averaging the fitted values over the data used in the fit. Adjusted data points are computed by adding the residual to the adjusted fitted value for each observation.
Plot the adjusted responses of a fitted linear model.
Load the carsmall data and fit a linear model of the mileage as a function of model year, weight, and weight squared.
load carsmall ds = dataset(MPG,Weight); ds.Year = ordinal(Model_Year); mdl = fitlm(ds,'MPG ~ Year + Weight^2');
Plot the effect of 'Weight' averaged over Year values.
Plot the effect of Year averaged over 'Weight' values. Include the h output.
h = plotAdjustedResponse(mdl,'Year');
Change the adjusted data to black x instead of red o.