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plotResiduals

Plot residuals of multinomial regression model

Since R2023a

    Description

    plotResiduals(mdl) generates a probability density plot of the deviance residuals for the multinomial regression model object mdl.

    example

    plotResiduals(mdl,plotType) specifies the residual plot type.

    example

    plotResiduals(ax,___) plots on the axes specified by ax instead of the current axes, using any of the input argument combinations in previous syntaxes.

    plotResiduals(___,Name=Value) specifies additional options using one or more name-value arguments. For example, you can specify the type of residuals to plot and the colors of the plotted objects.

    h = plotResiduals(___) returns graphics objects for the lines or patch in the plot. Use h to modify the properties of a specific line or patch after you create the plot. For a list of properties, see Line Properties or Patch Properties.

    example

    Examples

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    Load the fisheriris sample data set.

    load fisheriris

    The column vector species contains three iris flower species: setosa, versicolor, and virginica. The matrix meas contains four types of measurements for the flowers: the length and width of sepals and petals in centimeters.

    Fit a multinomial regression model to predict the iris flower species using the measurements. Display the table of residuals for the fitted model.

    mdl = fitmnr(meas,species);
    mdl.Residuals
    ans=150×3 table
            Raw          Pearson      Deviance
        ___________    ___________    ________
    
        0    0    0    0    0    0       0    
        0    0    0    0    0    0       0    
        0    0    0    0    0    0       0    
        0    0    0    0    0    0       0    
        0    0    0    0    0    0       0    
        0    0    0    0    0    0       0    
        0    0    0    0    0    0       0    
        0    0    0    0    0    0       0    
        0    0    0    0    0    0       0    
        0    0    0    0    0    0       0    
        0    0    0    0    0    0       0    
        0    0    0    0    0    0       0    
        0    0    0    0    0    0       0    
        0    0    0    0    0    0       0    
        0    0    0    0    0    0       0    
        0    0    0    0    0    0       0    
          ⋮
    
    

    The output shows the raw, Pearson, and deviance residuals for the model.

    Generate a probability density plot of the deviance residuals.

    plotResiduals(mdl)

    Figure contains an axes object. The axes object with title Histogram of residuals, xlabel Residuals, ylabel Probability density contains an object of type patch.

    The histogram shows that most of the deviance residuals are small. However, several residuals are greater than one.

    Inspect the observations with larger residuals. Sort the residuals from largest to smallest by using the sort function. Use the head function to display the four largest residuals and their corresponding indices.

    [r, ind] = sort(mdl.Residuals.Deviance,"descend");
    head(r,4)
        4.0443
        3.1707
        1.0378
        0.8035
    
    head(ind,4)
        84
       134
        71
       139
    

    The outputs show that observations corresponding to rows 84, 134, and 71 of meas and species have residuals larger than one. Given that most other residuals are close to zero, observations 84, 134, and 71 are most likely outliers.

    Load the carbig sample data set.

    load carbig

    The vectors Displacement, Cylinders, and Model_Year contain data for car engine displacement, number of engine cylinders, and year the car was manufactured, respectively.

    Fit a multinomial regression model using Displacement and Cylinders as predictors variables and Model_Year as the response.

    mdl = fitmnr([Displacement Cylinders],Model_Year);

    To determine whether the residuals are random, generate a lagged plot of the deviance residuals.

    plotResiduals(mdl,"lagged")

    Figure contains an axes object. The axes object with title Plot of residuals vs. lagged residuals, xlabel Residual(t-1), ylabel Residual(t) contains 3 objects of type line. One or more of the lines displays its values using only markers

    The lagged plot of the deviance residuals shows a cluster of residuals trending toward the top right of the plot. The cluster indicates a mildly positive correlation between the residual for a data point and the residual for the previous data point, suggesting that the residuals might not be random.

    Load the carbig sample data set.

    load carbig

    The vectors Displacement, Cylinders, and Model_Year contain of data for car engine displacement, number of engine cylinders, and year the car was manufactured, respectively.

    Fit a nominal multinomial regression model using Displacement and Cylinders as predictors variables and Model_Year as the response.

    mdl = fitmnr([Displacement Cylinders],Model_Year);

    mdl is a multinomial regression model object that contains the results of fitting a nominal multinomial regression model to the data.

    Display the name of the first response category.

    mdl.ClassNames(1)
    ans = 
    70
    

    The output shows that the first response category corresponds to cars manufactured in 1970.

    To determine whether the raw residuals for cars manufactured in 1970 are randomly distributed, create a probability plot and return a graphics array of the plotted objects. By default, plotResiduals uses the raw residuals for the first response category to create the probability plot.

    h = plotResiduals(mdl,"probability",ResidualType="raw")
    h = 
      2x1 graphics array:
    
      Line            (main)
      FunctionLine
    
    

    The output shows the data types for the elements in the graphics array h. The Line element corresponds to the raw residuals. The FunctionLine element corresponds to the line representing the theoretical normal distribution.

    Specify the color red for the normal distribution line by modifying the Color property of the second element in h.

    h(2).Color = "r"

    Figure contains an axes object. The axes object with title Normal probability plot of residuals, xlabel Residuals, ylabel Probability contains 2 objects of type functionline, line. One or more of the lines displays its values using only markers

    h = 
      2x1 graphics array:
    
      Line            (main)
      FunctionLine
    
    

    The plot shows that the residuals do not follow the red line, indicating that the raw residuals for cars manufactured in 1970 are not normally distributed.

    Input Arguments

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    Multinomial regression model object, specified as a MultinomialRegression model object created with the fitmnr function.

    Plot type, specified as one of the following values.

    ValueDescription
    "histogram"Probability density plot for residuals (default)
    "caseorder"Residuals versus case (row) order
    "fitted"Residuals versus fitted class scores
    "lagged"Residuals versus lagged residuals—that is, r(i) versus r(i – 1), where r(i) is the residual for the ith data point
    "probability"Normal probability plot
    "observed"Observed versus fitted values. This plot includes a dotted reference line of y = x. Each residual is represented by the vertical distance from the corresponding observed value to the reference line.
    "symmetry" Symmetry plot

    Example: "lagged"

    Data Types: char | string

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

    Name-Value Arguments

    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.

    Example: plotResiduals(mdl,ResidualType="Pearson",ClassToPlot="virginica",FaceColor="m") generates a magenta histogram for the Pearson residuals of the virginica response category.

    Residuals

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    Type of residual to plot, specified as one of the options in the following table.

    OptionDescription
    "deviance"Deviance residuals (default)
    "raw"

    Raw residuals, which are the observed values minus the fitted values

    "Pearson"

    Pearson residuals, which are the raw residuals divided by the root mean squared error (RMSE)

    For more information about each residual type, see Residuals.

    Example: ResidualType="raw"

    Data Types: char | string

    Residual response category to plot, specified as the name of a response category used to fit mdl. You can view the list of response category names by using the property mdl.ClassNames. The default value of ClassToPlot is mdl.ClassNames(1). This argument is valid only when ResidualType is "Pearson" or "raw".

    Example: ClassToPlot="virginica"

    Data Types: single | double | logical | char | cell | categorical

    Histogram Graphics

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    Face color, specified as "interp", "flat" an RGB triplet, a hexadecimal color code, a color name, or a short name.

    To designate a single color for all faces, specify FaceColor as an RGB triplet, a hexadecimal color code, a color name, or a short name.

    • 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 character vector or a string scalar 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. Thus, the color codes "#FF8800", "#ff8800", "#F80", and "#f80" are equivalent.

    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

    Here are the RGB triplets and hexadecimal color codes for the default colors MATLAB® uses in many types of plots.

    RGB TripletHexadecimal Color CodeAppearance
    [0 0.4470 0.7410]"#0072BD"

    Sample of RGB triplet [0 0.4470 0.7410], which appears as dark blue

    [0.8500 0.3250 0.0980]"#D95319"

    Sample of RGB triplet [0.8500 0.3250 0.0980], which appears as dark orange

    [0.9290 0.6940 0.1250]"#EDB120"

    Sample of RGB triplet [0.9290 0.6940 0.1250], which appears as dark yellow

    [0.4940 0.1840 0.5560]"#7E2F8E"

    Sample of RGB triplet [0.4940 0.1840 0.5560], which appears as dark purple

    [0.4660 0.6740 0.1880]"#77AC30"

    Sample of RGB triplet [0.4660 0.6740 0.1880], which appears as medium green

    [0.3010 0.7450 0.9330]"#4DBEEE"

    Sample of RGB triplet [0.3010 0.7450 0.9330], which appears as light blue

    [0.6350 0.0780 0.1840]"#A2142F"

    Sample of RGB triplet [0.6350 0.0780 0.1840], which appears as dark red

    Example: FaceColor="g"

    Data Types: single | double | char | string

    Face transparency, specified as one of these values:

    • Scalar in the range [0,1] — Use uniform transparency across all of the faces. A value of 1 is fully opaque and 0 is completely transparent. This option does not use the transparency values in the FaceVertexAlphaData property.

    • 'flat' — Use a different transparency for each face based on the values in the FaceVertexAlphaData property. First you must specify the FaceVertexAlphaData name-value argument as a vector containing one transparency value per face or vertex. The transparency value at the first vertex determines the transparency for the entire face.

    • 'interp' — Use interpolated transparency for each face based on the values in the FaceVertexAlphaData property. First you must specify the FaceVertexAlphaData name-value argument as a vector containing one transparency value per vertex. The transparency varies across each face by interpolating the values at the vertices.

    Example: FaceAlpha=0.5

    Data Types: single | double | char | string

    Line width, specified as a positive value in points, where 1 point = 1/72 of an inch. If the line has markers, then the line width also affects the marker edges.

    The line width cannot be thinner than the width of a pixel. If you set the line width to a value that is less than the width of a pixel on your system, the line appears as one pixel wide.

    Example: LineWidth=1.5

    Data Types: single | double

    Note

    The graphics properties for histograms listed here are only a subset. For a complete list, see Patch Properties.

    Line Graphics

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    Line color, specified as an RGB triplet, a hexadecimal color code, a color name, or a short name. The default value of [0 0 0] corresponds to black.

    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 character vector or a string scalar 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 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

    Here are the RGB triplets and hexadecimal color codes for the default colors MATLAB uses in many types of plots.

    RGB TripletHexadecimal Color CodeAppearance
    [0 0.4470 0.7410]"#0072BD"

    Sample of RGB triplet [0 0.4470 0.7410], which appears as dark blue

    [0.8500 0.3250 0.0980]"#D95319"

    Sample of RGB triplet [0.8500 0.3250 0.0980], which appears as dark orange

    [0.9290 0.6940 0.1250]"#EDB120"

    Sample of RGB triplet [0.9290 0.6940 0.1250], which appears as dark yellow

    [0.4940 0.1840 0.5560]"#7E2F8E"

    Sample of RGB triplet [0.4940 0.1840 0.5560], which appears as dark purple

    [0.4660 0.6740 0.1880]"#77AC30"

    Sample of RGB triplet [0.4660 0.6740 0.1880], which appears as medium green

    [0.3010 0.7450 0.9330]"#4DBEEE"

    Sample of RGB triplet [0.3010 0.7450 0.9330], which appears as light blue

    [0.6350 0.0780 0.1840]"#A2142F"

    Sample of RGB triplet [0.6350 0.0780 0.1840], which appears as dark red

    Example: Color="blue"

    Example: Color=[0 0 1]

    Example: Color="#0000FF"

    Data Types: single | double | char | string

    Line style, specified as one of the options listed in this table.

    Line StyleDescriptionResulting Line
    "-"Solid line

    Sample of solid line

    "--"Dashed line

    Sample of dashed line

    ":"Dotted line

    Sample of dotted line

    "-."Dash-dotted line

    Sample of dash-dotted line, with alternating dashes and dots

    "none"No lineNo line

    Example: LineStyle="--"

    Data Types: char | string

    Marker symbol, specified as one of the values listed in this table. By default, the object does not display markers. Specifying a marker symbol adds markers at each data point or vertex.

    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 line 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="x"

    Data Types: char | string

    Note

    The graphics properties for lines listed here are only a subset. For a complete list, see Line Properties.

    Output Arguments

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    Handle to the plotted objects, returned as a Patch object or a graphics array.

    When plotType is "Histogram", h is a Patch object. Otherwise, h is a graphics array. The contents of the graphics array depend on the value of plotType.

    plotType ValueContents of Graphics Array
    "caseorder"[Line; Line]
    "lagged"[Line; Line; Line]
    "probability"[Line; FunctionLine]
    "symmetry"[Line; Line]

    Version History

    Introduced in R2023a

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