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ecp (version 3.1.5)

Non-Parametric Multiple Change-Point Analysis of Multivariate Data

Description

Implements various procedures for finding multiple change-points from Matteson D. et al (2013) , Zhang W. et al (2017) , Arlot S. et al (2019). Two methods make use of dynamic programming and pruning, with no distributional assumptions other than the existence of certain absolute moments in one method. Hierarchical and exact search methods are included. All methods return the set of estimated change- points as well as other summary information.

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Version

Install

install.packages('ecp')

Monthly Downloads

3,756

Version

3.1.5

License

GPL (>= 2)

Maintainer

Wenyu Zhang

Last Published

July 1st, 2023

Functions in ecp (3.1.5)

ks.cp3o_delta

CHANGE POINTS ESTIMATION BY PRUNED OBJECTIVE (VIA KOLMOGOROV-SMIRNOV STATISTIC)
getWithin

GET WITHIN DISTANCE
process.data

PROCESS DATA
perm.cluster

PERMUTE CLUSTERS
splitPointC

SPLIT POINT-C
updateDistance

UPDATE DISTANCE
splitPoint

SPLIT POINT
gof.update

GOODNESS OF FIT UPDATE
ks.cp3o

CHANGE POINTS ESTIMATION BY PRUNED OBJECTIVE (VIA KOLMOGOROV-SMIRNOV STATISTIC)
kcpa

Kernel Change Point Analysis
sig.test

SIGNIFICANCE TEST
e.split

ENERGY SPLIT
find.closest

FIND CLOSEST CLUSTERS
DJIA

Dow Jones Industrial Average Index
getBetween

GET BETWEEN DISTANCE
ecp-internal

Internal Energy Change Point Functions
e.cp3o

CHANGE POINTS ESTIMATION BY PRUNED OBJECTIVE (VIA E-STATISTIC)
e.cp3o_delta

CHANGE POINTS ESTIMATION BY PRUNED OBJECTIVE (VIA E-STATISTIC)
e.divisive

ENERGY DIVISIVE
ACGH

Bladder Tumor Micro-Array Data
e.agglo

ENERGY AGGLOMERATIVE