Rpcop (version 1.1)

pcop: pcop

Description

Computes a principal curve of oriented points as defined in Delicado (2001).

Usage

pcop(x, Ch = 1.5, Cd = 0.3, plot.true = FALSE, ...)

Value

A list with two data frames. One contains a list with the following names: 'param': Value of the parameter t such the the principal oriented point is PCOP(t). 'dens': Density estimation for the random variable induced over the PCOP at t. 'span': proportion of original data involved in the determination of the principal oriented point. 'orth.var': Variance over the hyperplane orthogonal to the PCOP at the principal oriented point. 'pop': a p-dimensional array. The p coordinates of the principal oriented point. 'pr.dir': a p-dimensional array. The p coordinates of the principal direction for the principal oriented point. For the second, look at the package princurve.

Arguments

x

a matrix of n points in dimension p

Ch

The smoothing parameter h is C_H times the value given by the normal reference rule. Default value 1.5. Constraints 0.5 <= C_H <= 1.5

Cd

The distance between two consecutive principal oriented points in a PCOP is about C_D times the value of the smoothing parameter h. Default value 0.3. Constraints 0.25 <= C_D <= .5

plot.true

if TRUE, the function produces a plot

...

Additional parameters passed to function "lines"

Examples

x <- runif(100,-1,1)
x <- cbind(x, x ^ 2 + rnorm(100, sd = 0.1))
pcop(x, plot.true=TRUE, lwd=4, col=2)