hus.gibbs: Gibbs Sampler for Poisson Changepoint Model, Practical 11.6

In SMPracticals: Practicals for Use with Davison (2003) Statistical Models

Gibbs Sampler for Poisson Changepoint Model, Practical 11.6

Description

This function implements a Gibbs sampler for the Poisson changepoint model applied to the HUS data used in Example 4.40 and Practical 11.6 of Davison (2003), which should be consulted for details.

Usage

hus.gibbs(init, y, R = 10, a1 = 1, a2 = 1, c = 0.01, d = 0.01)

Arguments

init	Initial values for parameters
y	A series of Poisson counts
R	Number of iterations of sampler
a1	Value of a hyperparameter
a2	Value of a hyperparameter
c	Value of a hyperparameter
d	Value of a hyperparameter

Details

This is provided simply so that readers spend less time typing. It is not intended to be robust and general code.

Value

A matrix of size R x 7, whose first five columns contain the values of the parameters for the iterations. Columns 6 and 7 contain the log likelihood and log prior for that iteration.

Author(s)

Anthony Davison ([e-mail])

References

Davison, A. C. (2003) Statistical Models. Cambridge University Press. Practical 11.6.

Examples

## From Example 11.6:
hus <- c(1,5,3,2,2,1,0,0,2,1,1,7,11,4,7,10,16,16,9,15)
system.time( gibbs.out <- hus.gibbs(c(5, 5, 1, 1, 2), hus, R=1000))
plot.ts(gibbs.out[,1], main="lambda1") # time series plot for lam1
plot.ts(gibbs.out[,2], main="lambda1") # time series plot for lam2
plot.ts(gibbs.out[,6], main="log lik") # and of log likelihood
table(gibbs.out[,5])  # tabulate observed values of tau
rm(hus)

SMPracticals documentation built on May 29, 2024, 12:19 p.m.