est.mesa.model {SpatioTemporal} | R Documentation

## Examples of `estimateSTmodel` structure

### Description

Example of a model structure holding parameter estimates for the model in `mesa.model` using `estimate.STmodel`. Estimation results are also provided for models including spatio-temporal covariates.

### Format

A list with elements, see the return description in `estimate.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

`estimate.STmodel` for parameter estimation.
`createSTmodel` for creation of the originating `STmodel` object.

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

### Examples

    ##load a model object
    data(mesa.model)

    ##create vector of initial values
    dim <- loglikeSTdim(mesa.model)
    x.init <- cbind(c( rep(2, dim$nparam.cov-1), 0),
                    c( rep(c(1,-3), dim$m+1), -3, 0))
    rownames(x.init) <- loglikeSTnames(mesa.model, all=FALSE)

    ## Not run:
      ##estimate parameters
      est.mesa.model <- estimate(mesa.model, x.init, hessian.all=TRUE)

    ## End(Not run)

    ##time consuming estimation, load pre-computed results instead
    data(est.mesa.model)

    #estimation results
    print(est.mesa.model)

    ##compare the estimated parameters for the two starting points
    est.mesa.model$summary$par.all
    ##and values of the likelihood (and convergence info)
    est.mesa.model$summary$status

    ##extract the estimated parameters and approximate uncertainties
    x <- coef(est.mesa.model)

    ##compare estimated parameters
    ##plot the estimated parameters with uncertainties
    par(mfrow=c(1,1),mar=c(13.5,2.5,.5,.5))
    with(x, plot(par, ylim=range(c(par-1.96*sd, par+1.96*sd)),
                    xlab="", xaxt="n"))
    with(x, points(par - 1.96*sd, pch=3))
    with(x, points(par + 1.96*sd, pch=3))

    abline(h=0, col="grey")
    ##add axis labels
    axis(1, 1:length(x$par), rownames(x), las=2)

    ## Not run:
      ##example using a few fixed parameters
      x.fixed <- coef(est.mesa.model)$par
      x.fixed[c(1,2,5:9)] <- NA
      est.fix <- estimate(mesa.model, x.init, x.fixed, type="p")

    ## End(Not run)

[Package SpatioTemporal version 1.1.9.1 Index]