# StepSignalMargiLike-package: Estimating Change Points Using Marginal Likelihood In StepSignalMargiLike: Step-Wise Signal Extraction via Marginal Likelihood

## Description

(See the Manual.pdf file in data folder for a detail description of all functions, and a walkthrough tutorial.)

This packages provides function to estimate multiple change points using marginal likelihood method proposed by Du, Kao and Kou (2015), which we would denoted as DKK2015 afterward. `est.changepoints ` estimates change-points. `PlotChangePoints` plots. Other functions are for the normal and Poisson examples in DKK2015.

## Details

 Package: StepSignalMargiLike Type: Package Version: 2.5.9 Date: 2017-8-22 License: GNU GENERAL PUBLIC LICENSE Version 3, 29 June 2007

## Author(s)

Chao Du, Chu-Lan Michael Kao, Samuel Kou

Maintainer: Chu-Lan Michael Kao <chulankao@gmail.com>

## References

Chao Du, Chu-Lan Michael Kao and S. C. Kou (2016), "Stepwise Signal Extraction via Marginal Likelihood"

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18``` ```n <- 5 data.x <- rnorm(n, 1, 1) data.x <- c(data.x, rnorm(n, 10,1)) data.x <- c(data.x, rnorm(n, 2,1)) data.x <- c(data.x, rnorm(n, 10,1)) data.x <- c(data.x, rnorm(n, 1,1)) data.t <- 1:(5*n) prior <- prior.norm.A(data.x) max.segs <- 10 index.ChPT <- est.changepoints(data.x, mode="normal", prior) est.mean <- est.mean.norm(data.x, index.ChPT, prior) PlotChangePoints(data.x, data.t, index.ChPT, est.mean) PlotChangePoints(data.x, data.t, index.ChPT, est.mean, type.data="p", col.data="green", col.est="black", main="Stepwise Signal Estimation", sub="Using Marginal Likelihood", xlab="time", ylab="value") ```

StepSignalMargiLike documentation built on May 2, 2019, 1:02 p.m.