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plotAdjustedResponse

Adjusted response plot of linear regression model

Description

plotAdjustedResponse(mdl,var) creates an adjusted response plot for the variable var in the linear regression model mdl.

example

plotAdjustedResponse(mdl,var,Name,Value) specifies additional options using one or more name-value arguments. For example, you can specify the marker symbol and size for the data points.

plotAdjustedResponse(ax,___) plots into the axes specified by ax instead of the current axes (gca) using any of the input argument combinations in the previous syntaxes. (since R2024a)

h = plotAdjustedResponse(___) returns line objects. Use h to modify the properties of a specific line after you create the plot. For a list of properties, see Line Properties.

Examples

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Load the carsmall data set and fit a linear model of the mileage as a function of model year, weight, and weight squared.

load carsmall
tbl = table(MPG,Weight);
tbl.Year = categorical(Model_Year);
mdl = fitlm(tbl,'MPG ~ Year + Weight^2');

Plot the effect of Weight averaged over Year.

plotAdjustedResponse(mdl,'Weight')

Figure contains an axes object. The axes object with title Adjusted Response Plot, xlabel Weight, ylabel Adjusted MPG contains 2 objects of type line. One or more of the lines displays its values using only markers These objects represent Adjusted data, Adjusted fit.

Plot the effect of Year averaged over Weight.

plotAdjustedResponse(mdl,'Year');

Figure contains an axes object. The axes object with title Adjusted Response Plot, xlabel Year, ylabel Adjusted MPG contains 2 objects of type line. One or more of the lines displays its values using only markers These objects represent Adjusted data, Adjusted fit.

Input Arguments

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Linear regression model, specified as a LinearModel object created using fitlm or stepwiselm.

Variable for the adjusted response plot, specified as a character vector or string array of a name in mdl.PredictorNames, or a positive integer representing the index of a predictor from the names in mdl.VariableNames.

Data Types: char | string | single | double

Since R2024a

Target axes, specified as an Axes object. If you do not specify the axes, then plotAdjustedResponse uses the current axes (gca).

Name-Value Arguments

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Specify optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

Before R2021a, use commas to separate each name and value, and enclose Name in quotes.

Example: 'Color','blue','Marker','*'

Note

The graphical properties listed here are only a subset. For a complete list, see Line Properties. The specified properties determine the appearance of adjusted response data points.

Line color, specified an RGB triplet, hexadecimal color code, color name, or short name for one of the color options listed in the following table.

The Color name-value argument also determines marker outline color and marker fill color if MarkerEdgeColor is "auto" (default) and MarkerFaceColor is "auto".

For a custom color, specify an RGB triplet or a hexadecimal color code.

  • An RGB triplet is a three-element row vector whose elements specify the intensities of the red, green, and blue components of the color. The intensities must be in the range [0,1], for example, [0.4 0.6 0.7].

  • A hexadecimal color code is a string scalar or character vector that starts with a hash symbol (#) followed by three or six hexadecimal digits, which can range from 0 to F. The values are not case sensitive. Therefore, the color codes "#FF8800", "#ff8800", "#F80", and "#f80" are equivalent.

Alternatively, you can specify some common colors by name. This table lists the named color options, the equivalent RGB triplets, and the hexadecimal color codes.

Color NameShort NameRGB TripletHexadecimal Color CodeAppearance
"red""r"[1 0 0]"#FF0000"

Sample of the color red

"green""g"[0 1 0]"#00FF00"

Sample of the color green

"blue""b"[0 0 1]"#0000FF"

Sample of the color blue

"cyan" "c"[0 1 1]"#00FFFF"

Sample of the color cyan

"magenta""m"[1 0 1]"#FF00FF"

Sample of the color magenta

"yellow""y"[1 1 0]"#FFFF00"

Sample of the color yellow

"black""k"[0 0 0]"#000000"

Sample of the color black

"white""w"[1 1 1]"#FFFFFF"

Sample of the color white

"none"Not applicableNot applicableNot applicableNo color

This table lists the default color palettes for plots in the light and dark themes.

PalettePalette Colors

"gem" — Light theme default

Before R2025a: Most plots use these colors by default.

Sample of the "gem" color palette

"glow" — Dark theme default

Sample of the "glow" color palette

You can get the RGB triplets and hexadecimal color codes for these palettes using the orderedcolors and rgb2hex functions. For example, get the RGB triplets for the "gem" palette and convert them to hexadecimal color codes.

RGB = orderedcolors("gem");
H = rgb2hex(RGB);

Before R2023b: Get the RGB triplets using RGB = get(groot,"FactoryAxesColorOrder").

Before R2024a: Get the hexadecimal color codes using H = compose("#%02X%02X%02X",round(RGB*255)).

Example: Color="blue"

Data Types: single | double | string | char

Line width, specified as a positive value in points. If the line has markers, then the line width also affects the marker edges.

Example: LineWidth=0.75

Data Types: single | double

Marker symbol, specified as one of the values in this table.

MarkerDescriptionResulting Marker
"o"Circle

Sample of circle marker

"+"Plus sign

Sample of plus sign marker

"*"Asterisk

Sample of asterisk marker

"."Point

Sample of point marker

"x"Cross

Sample of cross marker

"_"Horizontal line

Sample of horizontal line marker

"|"Vertical line

Sample of vertical line marker

"square"Square

Sample of square marker

"diamond"Diamond

Sample of diamond marker

"^"Upward-pointing triangle

Sample of upward-pointing triangle marker

"v"Downward-pointing triangle

Sample of downward-pointing triangle marker

">"Right-pointing triangle

Sample of right-pointing triangle marker

"<"Left-pointing triangle

Sample of left-pointing triangle marker

"pentagram"Pentagram

Sample of pentagram marker

"hexagram"Hexagram

Sample of hexagram marker

"none"No markersNot applicable

Example: Marker="+"

Data Types: string | char

Marker outline color, specified an RGB triplet, hexadecimal color code, color name, or short name for one of the color options listed in the Color name-value argument.

The default value "auto" uses the same color specified by using the Color name-value argument. You can also specify "none" for no color.

Example: MarkerEdgeColor="blue"

Data Types: single | double | string | char

Marker fill color, specified as an RGB triplet, hexadecimal color code, color name, or short name for one of the color options listed in the Color name-value argument. The default value "none" specifies no color.

The "auto" value uses the same color specified by using the Color name-value argument.

Example: MarkerFaceColor="blue"

Data Types: single | double | string | char

Marker size, specified as a positive value in points.

Example: MarkerSize=2

Data Types: single | double

Output Arguments

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Line objects, returned as a 2-by-1 vector. h(1) corresponds to the adjusted response data points, and h(2) corresponds to the adjusted response function. Use dot notation to query and set properties of the line objects. For details, see Line Properties.

You can use name-value pair arguments to specify the appearance of adjusted response data points corresponding to the first graphics object h(1).

More About

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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.

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, 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.

  • plotPartialDependence creates either a line plot or a surface plot of predicted responses against a single feature or a pair of features, respectively, by marginalizing over the other variables. A line plot for a single feature from plotPartialDependence and an adjusted response function plot from plotAdjustedResponse are the same within numerical precision.

  • plotEffects creates a summary plot that shows separate effects for all predictors.

  • 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.

Extended Capabilities

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Version History

Introduced in R2012a

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