MCMC.mesa.model {SpatioTemporal} | R Documentation

## 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`.

### Source

Contains parametere estimates for the Spatio-Temporal model applied to monitoring data from the MESA Air project, see Cohen et.al. (2009) and `mesa.data.raw` for details.

### 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

    ##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)

    ## End(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")
    }

[Package SpatioTemporal version 1.1.9.1 Index]