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Plot method for eda_npol objects

Source: R/plot.eda_npol.R
plot.eda_npol.Rd

Generates either a variability decomposition plot of factor effects or a diagnostic plot for an object of class eda_npol.

Usage

# S3 method for class 'eda_npol'
plot(
  x,
  plot = "effects",
  reg = TRUE,
  margin = "residuals",
  legend = TRUE,
  legend.pos = "bottomright",
  legend.inset = 0.03,
  ...
)

Arguments

x

An object of class eda_npol.

plot

A character string specifying the type of plot to generate.

"effects" (default)

Generates a variability decomposition plot showing residuals and factor effects.

"diagnostic"

Generates a diagnostic plot. Its behavior is controlled by the margin argument.

reg

Logical. If TRUE, fits a linear regression line to the diagnostic plot. Only used when plot = "diagnostic". This is disabled when margin = "all". Defaults to FALSE.

margin

Character string. Only used when plot = "diagnostic". Specifies which diagnostic plot to generate. Can be the name of a two-way interaction (e.g., "Load:Length"), "residuals" (the default), or "all" to overlay all two-way interaction diagnostics.

legend

Logical. If TRUE, legend is added to plot when margin = "all".

legend.pos

The position of the legend when margin = "all". Can be "bottomright", "bottom", "bottomleft", "left", "topleft", "top", "topright", "right" and "center". Defaults to "topright".

legend.inset

The amount of inset for the legend from the plot border when margin = "all". Defaults to 0.03.

...

Additional arguments passed to internal plotting functions.

Value

A plot is generated on the active graphics device. The function itself returns NULL.

Details

This method generates two types of plots for eda_npol objects:

1. Variability Decomposition Plot (plot = "effects")
Visualizes residuals and the spread of all fitted effects. Calls .eda_plot_vardecomp.

2. Diagnostic Plot (plot = "diagnostic")
When used with an object from eda_npol, this plot's behavior is controlled by the margin argument. Calls .eda_plot_xy.

  • margin = "residuals": Plots final residuals against their n-way comparison values to diagnose higher-order non-additivity.

  • margin = "FactorA:FactorB": Plots the fitted two-way interaction effects against their specific comparison values.

  • margin = "all": Overlays the diagnostic plots for all two-way interactions onto a single graph, with each interaction represented by a different color and symbol.

For a main-effect only model, this generates a single diagnostic plot of residuals versus a composite comparison value.

See also

eda_npol, .eda_plot_vardecomp, .eda_plot_xy

Examples


# Main effect median polish (i.e. no interaction)
M1 <- eda_npol(yarn, Cycles, Load, Length, Amplitude)
plot(M1) # Plot effect values and residuals

plot(M1, plot = "diagnostic") # Plot residuals vs comparison value

#>                int Comparison Value^1 
#>         114.231269           1.292551 

# Full effect median polish (i.e. include two-way interactions)
M2 <- eda_npol(yarn, Cycles, Load, Length, Amplitude, max_order = 2)
plot(M2, plot = "diagnostic") # Plot residuals vs higher-order CV

#>                int CV for residuals^1 
#>        -14.3106101          0.6090007 

# Overlay all two-way interaction diagnostics
plot(M2, plot = "diagnostic", margin = "all")
#> For 'margin = "all"', regression lines are disabled to avoid confusion.


# Generate the diagnostic plot for a specific two-way interaction
plot(M2, plot = "diagnostic", margin = "Load:Length", reg = TRUE)

#>                  int CV for Load:Length^1 
#>            1.9248763            0.9706704 

# Generate side-by-side diagnostic plots for all two-way interactions
numplots <- length(M2$cv) - 1
nameplots <- names(M2$cv)[-(numplots+1)]
nc <- ceiling(sqrt(numplots))      # number of columns
nr <- ceiling(numplots / nc)       # number of row
OP <- par(mfrow=c(nr,nc))
invisible(sapply(nameplots, \(x) plot(M2, plot="diagnostic", margin = x, reg=TRUE)))
#>                  int CV for Load:Length^1 
#>            1.9248763            0.9706704 
#>                     int CV for Load:Amplitude^1 
#>             -19.5494337               0.5854442 
#>                       int CV for Length:Amplitude^1 
#>                148.786019                  2.275077 
par(OP)