Non-parametric Multiple Change-points Detection

Description

Detect multiple change-points using a non-parametric maximum likelihood approach.

Usage

1
nmcd(x, kmax, cpp, ncp = length(cpp), n)

Arguments

x

data vector

kmax

upper bound of the number of change-points

cpp

positions of candidate change-points. usually returned by functionisp. if this parameter is not assigned, the isp function will be called to assign it.

ncp

the number of the candidate change-points.

n

length of the data.

Details

NMCD use DP algorithm to select change-points, while the true number of change-points is determined by the Bayesian information criterion(BIC).

Value

a list with class nmcd is returned with elements:

npp

the true number of change-points

cpp

positions of true change-points

data

raw data, this is not printed on screen by default

bic

minimal BIC value gained.

Note

memory consume may be significant with large data.

References

Changliang Zou, Guosheng Yin, Long Feng, Zhaojun Wang. Non-parametric Maximum Likelihood Approach to Multiple Change-points Problem

Examples

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