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ecp (version 3.1.6)

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

2,186

Version

3.1.6

License

GPL (>= 2)

Maintainer

Wenyu Zhang

Last Published

August 26th, 2024

Functions in ecp (3.1.6)

perm.cluster

PERMUTE CLUSTERS
updateDistance

UPDATE DISTANCE
e.split

ENERGY SPLIT
getBetween

GET BETWEEN DISTANCE
ACGH

Bladder Tumor Micro-Array Data
process.data

PROCESS DATA
DJIA

Dow Jones Industrial Average Index
find.closest

FIND CLOSEST CLUSTERS
splitPoint

SPLIT POINT
e.cp3o

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

ENERGY DIVISIVE
kcpa

Kernel Change Point Analysis
splitPointC

SPLIT POINT-C
sig.test

SIGNIFICANCE TEST
ecp-internal

Internal Energy Change Point Functions
e.cp3o_delta

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

ENERGY AGGLOMERATIVE
ks.cp3o_delta

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

GET WITHIN DISTANCE
ks.cp3o

CHANGE POINTS ESTIMATION BY PRUNED OBJECTIVE (VIA KOLMOGOROV-SMIRNOV STATISTIC)
gof.update

GOODNESS OF FIT UPDATE