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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 = FALSE, ...)

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 scatterplot of residuals versus comparison values (CV).

reg

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

...

Additional arguments passed to internal plotting functions.

For plot = "effects"

Arguments are passed to .eda_plot_vardecomp. Common options include:

  • rotate: Logical. Rotate plot orientation.

  • show.resp: Logical. Include boxplot of the centered response.

  • outliers: Logical. Show outliers in boxplots.

  • label: Logical. Label individual effect levels.

  • order: Logical. Order effects by spread.

  • cex.txt: Numeric. Text size for labels.

  • lim: Numeric vector. Axis limits.

  • overlap: Character. One of "stack", "overplot", or "jitter".

  • grey: Numeric or character. Grayscale coloring.

  • type: Character. Plot type, e.g., "boxpnt" or "box".

  • input: Character. Either "nway" or "reg".

  • padding: Numeric. Padding for axis limits.

For plot = "diagnostic"

Arguments are passed to .eda_plot_xy. Common options include:

  • xlab, ylab: Axis labels.

  • xlim, ylim: Axis limits.

  • poly: Integer. Degree of polynomial regression.

  • robust: Logical. Use robust regression.

  • w: Numeric vector. Weights for regression.

  • sd, mean.l: Logical. Show ±1 SD and mean lines.

  • asp, square: Logical. Control aspect ratio and plot shape.

  • grey: Numeric. Grayscale background.

  • pch, p.col, p.fill, size, alpha: Point styling.

  • q, inner, q.type, qcol: Quantile box options.

  • loe, loe.col, loe.lw, loess.d: Loess smoothing options.

  • lm.col, lm.lw: Regression line styling.

  • stats, stat.size: Display model statistics.

  • hline, vline: Reference lines.

  • rlm.d: List. Parameters for MASS::rlm.

Value

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

Details

This method serves as a wrapper to generate two types of plots for eda_npol objects:

1. Variability Decomposition Plot (plot = "effects")
Calls .eda_plot_vardecomp to visualize residuals and factor effects. Useful for assessing the relative magnitude and spread of effects and identifying outliers.

2. Diagnostic Plot (plot = "diagnostic")
Calls .eda_plot_xy to plot residuals against comparison values (CV). Useful for detecting nonadditivity or model misfit. Optional regression and smoothing lines can be added.

See also

.eda_plot_vardecomp, .eda_plot_xy

Examples


# Generate eda_npol object
M0 <- eda_npol(yarn, Cycles, Load, Length, Amplitude)

# Plot effects (default)
plot(M0)


# Add labels
plot(M0, label = TRUE)


# Rotate plot
plot(M0, rotate = TRUE)


# Add boxplot of centered response variable
plot(M0, show.resp = TRUE)


# Generate diagnostic plot (residuals vs CV)
plot(M0, plot = "diagnostic")


# Fit a robust regression line to diagnostic plot
# The function displays the line's slope in the console
plot(M0, plot = "diagnostic", reg = TRUE, robust = TRUE, loe = FALSE)

#>                int Comparison Value^1 
#>         30.7565973          0.6813374