find.closest: FIND CLOSEST CLUSTERS

In ecp: Non-Parametric Multiple Change-Point Analysis of Multivariate Data

FIND CLOSEST CLUSTERS

Description

Determines which two segments to merge.

Usage

find.closest(K, ret)

Arguments

K	Integer indicating the progress of the agglomerative process.
ret	A list with 'open', 'N', and 'right' components

Details

This method is called by the e.agglomerative method, and should not be called by the user.

Value

Returns a vector with 3 components. The first two indicate which segments are to be merged. The third is the new goodness of fit statistics.

Author(s)

Nicholas A. James

References

James NA, Matteson DS (2013). A Nonparametric Approach for Multiple Change Point Analysis of Multivariate Data.

Nicholas A. James, David S. Matteson (2014). "ecp: An R Package for Nonparametric Multiple Change Point Analysis of Multivariate Data.", "Journal of Statistical Software, 62(7), 1-25", URL "http://www.jstatsoft.org/v62/i07/"

Rizzo ML, Szekely GL (2005). Hierarchical clustering via joint between-within distances: Extending ward's minimum variance method. Journal of Classification. pp. 151 - 183.

See Also

e.agglo

ecp documentation built on Sept. 12, 2024, 7:40 a.m.