plotDiagnostics
Plot observation diagnostics of linear regression model
Syntax
Description
plotDiagnostics
creates a plot of observation diagnostics
such as leverage, Cook's distance, and delete-1 statistics to identify outliers and
influential observations.
plotDiagnostics(
creates a leverage
plot of the linear regression model (mdl
)mdl
) observations. A
dotted line in the plot represents the recommended threshold values.
plotDiagnostics(
specifies the graphical properties of diagnostic 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
,plottype
,Name,Value
)
returns graphics objects for the lines or contour in the plot using any of the input
argument combination in the previous syntaxes. Use h
= plotDiagnostics(___)h
to modify
the properties of a specific line or contour after you create the plot. For a list
of properties, see Line Properties and Contour Properties.
Examples
Input Arguments
Output Arguments
More About
Tips
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.
Use
legend('show')
to show the pre-populated legend.
Alternative Functionality
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, useplotResiduals
to analyze the residuals of the model.After fitting a model, use
plotAdjustedResponse
,plotPartialDependence
, andplotEffects
to understand the effect of a particular predictor. UseplotInteraction
to understand the interaction effect between two predictors. Also, useplotSlice
to plot slices through the prediction surface.
References
[1] Neter, J., M. H. Kutner, C. J. Nachtsheim, and W. Wasserman. Applied Linear Statistical Models, Fourth Edition. Chicago: McGraw-Hill Irwin, 1996.
Extended Capabilities
Version History
Introduced in R2012a