Segmentation of an AR(1) Gaussian process

Description

This package consists in an implementation of a robust approach to solve the problem of multiple change-point estimation in the mean of a Gaussian AR(1) process. A robust estimator of the autoregression parameter is proposed and used to build a decorrelated series on which a classical penalized least-square approach is applied.

Details

Author(s)

S. Chakar, E. Lebarbier, C. Levy-Leduc, S. Robin

Maintainer: Souhil Chakar <souhil.chakar@agroparistech.fr>

References

S. Chakar, E. Lebarbier, C. Levy-Leduc, S. Robin. A robust approach to multiple change-point estimation in an AR(1) process, arXiv:1403.1958.

Examples

library(AR1seg)
data(y)
res=AR1seg_func(y,Kmax=15,rho=TRUE)
a=c(1,res$PPSelectedBreaks[1:(res$PPselected-1)]+1)
b=res$PPSelectedBreaks[1:(res$PPselected)]
Bounds=cbind(a,b)
mu.fit=rep(res$PPmean,Bounds[,2]-Bounds[,1]+1)
plot(y)
lines(mu.fit,col="red")

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(AR1seg)
Loading required package: Segmentor3IsBack
Segmentor3IsBack v1.8 Loaded 

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/AR1seg/AR1seg-package.Rd_%03d_medium.png", width=480, height=480)
> ### Name: AR1seg-package
> ### Title: Segmentation of an AR(1) Gaussian process
> ### Aliases: AR1seg-package AR1seg
> 
> ### ** Examples
> 
> library(AR1seg)
> data(y)
> res=AR1seg_func(y,Kmax=15,rho=TRUE)
> a=c(1,res$PPSelectedBreaks[1:(res$PPselected-1)]+1)
> b=res$PPSelectedBreaks[1:(res$PPselected)]
> Bounds=cbind(a,b)
> mu.fit=rep(res$PPmean,Bounds[,2]-Bounds[,1]+1)
> plot(y)
> lines(mu.fit,col="red")
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>