triplot: triplot: 3D biplots for PCA and more

In abnormally-distributed/cvreg: Cross Validation and Robust Estimation Utilities

Description

triplot: 3D biplots for PCA and more

Usage

triplot(
  fit,
  choices = c(1, 2, 3),
  groups = NULL,
  ellipse = F,
  ellipse.prob = 0.95,
  scale = 1,
  pc.biplot = T,
  var.axes = T,
  var.names = T,
  obs.scale = 1 - scale,
  var.scale = scale,
  shape = NULL,
  size = c(s = 1, p = 4)
)

Arguments

fit	the model fit
choices	the components to plot
groups	optional group labels
ellipse	draw a gaussian data ellipse for each group?
ellipse.prob	size of the ellipse in gaussian probability
scale	covariance biplot (scale = 1), form biplot (scale = 0). when scale = 1, the inner product between the variables approximates the covariance and the distance between the points approximates the Mahalanobis distance.
pc.biplot	for compatibility with biplot.princomp()
var.axes	should loading arrows be drawn? defaults to TRUE.
obs.scale	scale factor to apply to observations
var.scale	scale factor to apply to variables
shape	one of "p" for 2 dimensional points, or "s" for spheres. if left as NULL, "s" is used for smaller sample sizes (N < 250) and "p" is used otherwise to ease computational load on computers without a dedicated GPU.
size	a vector of length 2 of sizes for the data. defaults to 1 for shperes and 4 for points. if only one number is provided, be sure to select which shape it goes with and don't leave shape as NULL.
var.labels	should the arrows be labeled? defaults to TRUE.

Value

an rgl plot

abnormally-distributed/cvreg documentation built on May 3, 2020, 3:45 p.m.