Edist.meas_singleh: Compute the Expected Distance in Measure (EDM) between a...

In AlessandroCasa/BsMc: Bandwidth selection for modal clustering

Description

Compute the Expected Distance in Measure (EDM) between a kernel estimator-induced partition and the population one defined by a K-component normal mixture density for a single bandwidth value.

Usage

Edist.meas_singleh(n = 100, h, mus = 0, sigmas = 1, props = 1,
  B = 100)

Arguments

n	sample size of the simulated Monte Carlo samples.
h	value of the bandwidth for which the EDM has to be computed.
mus	vector of means of the mixture components.
sigmas	vector of standard deviations of the mixture components.
props	vector of mixing proportions of the mixture components.
B	the number of Monte Carlo samples.

Value

the value of the EDM for the given value h

References

Chacón, J.E. (2015). A population background for nonparametric density-based clustering. Statistical Science 30(4): 518-532.

AlessandroCasa/BsMc documentation built on Oct. 30, 2019, 4:49 a.m.