kernels.and.distances: Auxiliary kernel and distance functions.

In LPCM: Local Principal Curve Methods

Auxiliary kernel and distance functions.

Description

Internal LPCM functions which are normally not to be called by the user.

Usage

kern(y, x = 0, h = 1)
kernd(X, x, h)
kdex(X, x, h)
distancevector(X, y, d = "euclid", na.rm = TRUE)
vecdist(X,Y)
mindist(X,y)
enorm(x)

Arguments

x	a number or vector.
y	a vector.
h	a bandwidth.
X	a matrix.
Y	a matrix.
d	type of distance measure (only ‘euclid’).
na.rm	...

Details

kern specifies the base kernel (by default Gaussian) used in lpc ; kernd is the corresponding multivariate product kernel. kdex is a pointwise multivariate kernel density estimator.

distancevector makes use of function vdisseuclid from R package hopach (but that package does not need to be loaded). enorm is the Euclidean norm.

Author(s)

JE

References

Pollard, van der Laan, and Wall (2010). Hierarchical Ordered Partitioning and Collapsing Hybrid (HOPACH). R package hopach version 2.9.1.

LPCM documentation built on Sept. 11, 2024, 7:53 p.m.