Added variable plot of linear regression model
plotAdded(
produces an added variable plot for the whole model mdl
)mdl
except
the constant (intercept) term.
plotAdded(
specifies graphical properties of adjusted data points using one or more name-value
pair arguments. For example, you can specify the marker symbol and size for the data
points.mdl
,coef
,Name,Value
)
returns
line objects using any of the input argument combinations in the previous syntaxes.
Use h
= plotAdded(___)h
to modify the properties of a specific line after you
create the plot. For a list of properties, see Line Properties.
The data cursor displays the values of the selected plot point in a data tip (small text box located next to the data point). The data tip includes the x-axis and y-axis values for the selected point, along with the observation name or number.
A LinearModel
object provides multiple plotting functions.
When creating a model, use plotAdded
to understand the effect of adding or removing a predictor
variable.
When verifying a model, use plotDiagnostics
to find questionable data and to understand the
effect of each observation. Also, use plotResiduals
to analyze the residuals of the model.
After fitting a model, use plotAdjustedResponse
, plotPartialDependence
, and plotEffects
to understand the effect of a particular predictor. Use
plotInteraction
to understand the
interaction effect between two predictors. Also, use plotSlice
to plot slices through the prediction surface.
plotAdded
shows the incremental effect on the response of specified
terms by removing the effects of the other terms, whereas
plotAdjustedResponse
shows the effect of a selected predictor in
the model fit with the other predictors averaged out by averaging the fitted values. Note
that the definitions of adjusted values in plotAdded
and
plotAdjustedResponse
are not the same.