SpatioTemporal (version 1.1.7)

MCMC.mesa.model: Example of a mcmcSTmodel structure

Description

The output from a Metropolis-Hastings algorithm, implemented in MCMC.STmodel), run for the model in mesa.model

Format

A list with elements, see the return description in MCMC.STmodel.

References

M. A. Cohen, S. D. Adar, R. W. Allen, E. Avol, C. L. Curl, T. Gould, D. Hardie, A. Ho, P. Kinney, T. V. Larson, P. D. Sampson, L. Sheppard, K. D. Stukovsky, S. S. Swan, L. S. Liu, J. D. Kaufman. (2009) Approach to Estimating Participant Pollutant Exposures in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Environmental Science & Technology: 43(13), 4687-4693.

See Also

createSTmodel for creation of the originating STmodel object.

Other example data: est.cv.mesa, est.mesa.model, mesa.data.raw, mesa.model, pred.mesa.model

Examples

# NOT RUN {
##load data
data(mesa.model)
##and results of estimation
data(est.mesa.model)

##strating point
x <- coef(est.mesa.model)
##Hessian, for use as proposal matrix
H <- est.mesa.model$res.best$hessian.all
# }
# NOT RUN {
  ##run MCMC
  MCMC.mesa.model <- MCMC(mesa.model, x$par, N = 2500, Hessian.prop = H)
# }
# NOT RUN {
##lets load precomputed results instead
data(MCMC.mesa.model)

##Examine the results
print(MCMC.mesa.model)

##and contens of result vector
names(MCMC.mesa.model)
 
##Summary
summary(MCMC.mesa.model)

##MCMC tracks for four of the parameters
par(mfrow=c(5,1),mar=c(2,2,2.5,.5))
plot(MCMC.mesa.model, ylab="", xlab="", type="l")
for(i in c(4,9,13,15)){
  plot(MCMC.mesa.model, i, ylab="", xlab="", type="l")
}
# }