findFd: Find f and delta from distance matrix.

In ethanyxu/ADPclust: Fast Clustering Using Adaptive Density Peak Detection

Find f and delta from distance matrix.

Description

Calculate f(x) and delta(x) from distm and h.

Usage

FindFD(distm, h, fdelta, f = NULL)

Arguments

distm	distance matrix of class 'dist'.
h	bandwidth.
fdelta	character string that specifies the method used to estimate local density f(x) at each data point x. The default is "mnorm" that uses a multivariate Gaussian density estimation to calculate f. Other options are listed below. Here 'distm' denotes the distance matrix.
f	numerical vector. Density values of data points. If not given (default) it is estimated by the method specified in "fdelta" unorm(f <- 1/(h * sqrt(2 * pi)) * rowSums(exp(-(distm/h)^2/2))); Univariate Gaussian smoother weighted(f <- rowSums(exp(-(distm/h)^2))); Univariate weighted smoother count(f <- rowSums(distm < h) - 1); Histogram estimator (used in Rodriguez [2014])

Value

list of two items: f and delta.

ethanyxu/ADPclust documentation built on June 3, 2022, 12:38 p.m.