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plotAdded

Class: LinearModel

Added variable plot or leverage plot for linear model

Syntax

plotAdded(mdl)
plotAdded(mdl,coef)
h = plotAdded(mdl,___)
h = plotAdded(mdl,coef,Name,Value)

Description

plotAdded(mdl) produces a generalized added variable plot for all terms in the full, fitted regression model mdl, except the constant term.

plotAdded(mdl,coef) produces an added variable plot for the coef terms in mdl, after adjusting for all other terms.

h = plotAdded(mdl,___) returns handles to the lines in the plot, using any of the previous syntaxes.

h = plotAdded(mdl,coef,Name,Value) plots with additional options specified by one or more Name,Value pair arguments.

Tips

  • 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.

Input Arguments

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Full, fitted linear regression model, specified as a LinearModel object constructed using fitlm or stepwiselm.

Coefficients in regression model mdl, specified as one of the following:

  • Character vector giving a single coefficient name

  • Vector of coefficient numbers in the mdl.CoefficientNames property.

Name-Value Pair Arguments

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.

    Note:   The plot property name-value pairs apply to the first returned handle h(1).

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Color of the line or marker, specified as the comma-separated pair consisting of 'Color' and a ColorSpec specification. For details, see linespec.

Line style, specified as the comma-separated pair consisting of 'LineStyle' and a Chart Line Properties specification. For details, see linespec.

Width of the line or edges of filled area, in points, specified as the comma-separated pair consisting of 'LineWidth' and a positive numeric value. One point is equal to 1/72 inch.

Color of the marker or edge color for filled markers, specified as the comma-separated pair consisting of 'MarkerEdgeColor' and a ColorSpec specification. For details, see linespec.

Color of the marker face for filled markers, specified as the comma-separated pair consisting of 'MarkerFaceColor' and a ColorSpec specification. For details, see linespec.

Size of the marker in points, specified as the comma-separated pair consisting of 'MarkerSize' and a positive numeric value. One point is 1/72 inch.

Output Arguments

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Graphics handles, returned as a vector of graphics handles corresponding to the lines or patches in the plot.

Definitions

Added Variable Plot and Adjusted Response

An added variable plot illustrates the incremental effect on the response of specified terms by removing the effects of all other terms. The slope of the fitted line is the coefficient of the linear combination of the specified terms projected onto the best-fitting direction. The adjusted response includes the constant (intercept) terms, and averages out all other terms.

Examples

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Create a model of car mileage as a function of weight and model year. Then create a plot to see the significance of the model.

Create a linear model of mileage from the carsmall data.

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

Create an added variable plot.

plot(mdl)

The plot illustrates that the model is significant because a horizontal line does not fit between the confidence bounds.

Create a model of car mileage as a function of weight and model year. Then create a plot to see the effect of the weight terms (Weight and Weight^2).

Create a linear model of mileage from the carsmall data.

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

Find the terms in the model corresponding to the Weight and Weight^2.

mdl.CoefficientNames
ans =

  1×5 cell array

    '(Intercept)'    'Weight'    'Year_76'    'Year_82'    'Weight^2'

The weight terms are 2 and 5.

Create an added variable plot with the weight terms.

coef = [2 5];
plotAdded(mdl,coef)

The plot illustrates that the weight terms are significant because a horizontal line does not fit between the confidence bounds.

Related Examples

See Also

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