PieceExpIntensity: Runs the PieceExpIntensity sampler and returns posterior...

In PieceExpIntensity: Bayesian Model to Find Changepoints Based on Rates and Count Data

Description

Returns a list of posterior samples along with summaries for the most visited number of split points.

Usage

PieceExpIntensity(X, Y, B, Poi)

Arguments

X	Vector containing observed event times.
Y	Vector containing poisson count intensities.
B	Number of iterations to run the MCMC with half burned in.
Poi	Prior mean number of split points.

Value

A list of all posterior quantities and a summary of the most commonly visited model.

References

Chapple (2017). Modeling ISIL terror attacks and their intensities via flexible Bayesian piecewise models. Currently Under Review.

Examples

B=1000
n=100
X=rexp(n,1)
Y=X
Y[X<.5]=rpois(sum(X<.5),20)
Y[X>.5]=rpois(sum(X>.5),3)
Poi=10
PieceExpIntensity(X,Y,B,Poi)

PieceExpIntensity documentation built on May 1, 2019, 9:26 p.m.