pairs.ridge: Scatterplot Matrix of Bivariate Ridge Trace Plots

In friendly/genridge: Generalized Ridge Trace Plots for Ridge Regression

Scatterplot Matrix of Bivariate Ridge Trace Plots

Description

Displays all possible pairs of bivariate ridge trace plots for a given set of predictors.

Usage

## S3 method for class 'ridge'
pairs(
  x,
  variables,
  radius = 1,
  lwd = 1,
  lty = 1,
  col = c("black", "red", "darkgreen", "blue", "darkcyan", "magenta", "brown",
    "darkgray"),
  center.pch = 16,
  center.cex = 1.25,
  digits = getOption("digits") - 3,
  diag.cex = 2,
  diag.panel = panel.label,
  fill = FALSE,
  fill.alpha = 0.3,
  ...
)

Arguments

x	A ridge object, as fit by ridge
variables	Predictors in the model to be displayed in the plot: an integer or character vector, giving the indices or names of the variables.
radius	Radius of the ellipse-generating circle for the covariance ellipsoids.
lwd, lty	Line width and line type for the covariance ellipsoids. Recycled as necessary.
col	A numeric or character vector giving the colors used to plot the covariance ellipsoids. Recycled as necessary.
center.pch	Plotting character used to show the bivariate ridge estimates. Recycled as necessary.
center.cex	Size of the plotting character for the bivariate ridge estimates
digits	Number of digits to be displayed as the (min, max) values in the diagonal panels
diag.cex	Character size for predictor labels in diagonal panels
diag.panel	Function to draw diagonal panels. Not yet implemented: just uses internal panel.label to write the variable name and ranges.
fill	Logical vector: Should the covariance ellipsoids be filled? Recycled as necessary.
fill.alpha	Numeric vector: alpha transparency value(s) for filled ellipsoids. Recycled as necessary.
...	Other arguments passed down

Value

None. Used for its side effect of plotting.

Author(s)

Michael Friendly

References

Friendly, M. (2013). The Generalized Ridge Trace Plot: Visualizing Bias and Precision. Journal of Computational and Graphical Statistics, 22(1), 50-68, doi:10.1080/10618600.2012.681237, https://www.datavis.ca/papers/genridge-jcgs.pdf

See Also

ridge for details on ridge regression as implemented here

plot.ridge, traceplot for other plotting methods

Examples

longley.y <- longley[, "Employed"]
longley.X <- data.matrix(longley[, c(2:6,1)])

lambda <- c(0, 0.005, 0.01, 0.02, 0.04, 0.08)
lridge <- ridge(longley.y, longley.X, lambda=lambda)

pairs(lridge, radius=0.5, diag.cex=1.75)

data(prostate)
py <- prostate[, "lpsa"]
pX <- data.matrix(prostate[, 1:8])
pridge <- ridge(py, pX, df=8:1)

pairs(pridge)

friendly/genridge documentation built on March 4, 2024, 3:22 a.m.