est.mean.pois: est.mean.pois

In StepSignalMargiLike: Step-Wise Signal Extraction via Marginal Likelihood

Description

This function estimates the posterior mean for each segments under the Poisson assumption with conjugate prior. The data is assumed to follow Poisson(λ), where λ is assumed to have Beta prior with shape parameters α and β.

Usage

est.mean.pois(data.x, index.ChPT, prior)

Arguments

data.x	Observed data in vector form where each element represents a single observation.
index.ChPT	The set of the index of change points in a vector. Must be in accending order. This could be obtained by est.changepoints.
prior	Vector contatining prior parameters in the order of (α, β)

.

Details

See Manual.pdf in "data" folder.

Value

Vector containing estimated mean for each segments.

References

Chao Du, Chu-Lan Michael Kao and S. C. Kou (2015), "Stepwise Signal Extraction via Marginal Likelihood". Forthcoming in Journal of American Statistical Association.

Examples

library(StepSignalMargiLike)

n <- 20
data.x <- rpois(n, 1)
data.x <- c(data.x, rpois(n, 10))
data.x <- c(data.x, rpois(n, 50))
data.x <- c(data.x, rpois(n, 20))
data.x <- c(data.x, rpois(n, 80))
data.x <- matrix(data.x,1)

prior <- c(1,2)
index.ChangePTs <- c(n, 2*n, 3*n, 4*n)
est.mean.pois(data.x, index.ChangePTs, prior)

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