pcurves: Principal Curves Analysis

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

Description

This is an alternative to the function contained in the princurv package. It is somewhat simpler to use by comparison. This implementation uses a robust smoother from the loess.smooth function by default.

Usage

pcurves(
  x,
  tol = 1e-05,
  maxit = 1000,
  stretch = 1.25,
  family = c("symmetric", "gaussian"),
  plot = FALSE
)

Arguments

x	A matrix or data frame of numeric variables.
tol	Convergence threshold on shortest distances to the curve.
maxit	Maximum number of iterations.
stretch	A stretch factor for the endpoints of the curve, allowing the curve to grow to avoid bunching at the end. Must be a numeric value between 0 and 2. Defaults to 1.25.
family	one of "symmetric" or "gaussian". defaults to "symmetric" which gives nearly identical results as the "gaussian" option, unless there are outliers, in which case "symmetric" gives better results. therefore the "symmetric" is typically the best option.
plot	Should the iterations be plotted? Defaults to FALSE.

Value

a list with class "principalCurves"

References

Hastie, T. and Stuetzle, W., Principal Curves, JASA, Vol. 84, No. 406 (Jun., 1989), pp. 502-516, DOI: 10.2307/2289936

Examples

pcurves(iris[,-5])

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