simJSS {ramps} | R Documentation |
Simulated Iowa, USA, areal and point-source measurements analyzed in the Working Example of the ramps package paper published in Journal of Statistical Software.
data(simJSS)
The following variables are provided in the simIowa
data frame:
areal
y
id
siteId
lon
lat
weights
A grid of coordinates is provided by the simGrid
data frame to facilitate Monte Carlo integration in geostatistical modeling of areal measurements. The included columns are
lon
lat
id
county
Areal measurements in simIowa
can be matched to the grid coordinates in simGrid
via the shared "id"
variable.
Areal and point-source observations were generated from from a geostatistical model using the county structure in the state of Iowa, USA. There are 99 counties in the state. Areal observations were generated from each as county averages from a uniform grid of 391 sites - approximately 4 sites per county. An additional 600 point-source observations were generated from a set of 300 unique sites sampled from a uniform distribution in Iowa.
An exponential correlation structure with a range parameter of 10 was used for the underlying Gaussian spatial structure. Measurement errors were generated with variances of 0.25 for point-source data and 0.09 for areal data. Site-specific non-spatial random effects were generated with a variance 0.16. One fixed effects covariate with coefficient equal to 0.5 was included as an indicator for areal observations.
Smith, B. J., Yan, J., and Cowles, M. K. (2008) “Unified Geostatistical Modeling for Data Fusion and Spatial Heteroskedasticity with R Package ramps”, Journal of Statistical Software, 25(10), 1-21.
data(simJSS) ## Map areal and point-source measurements y <- simIowa$y[simIowa$areal == 1] level <- (max(y) - y) / diff(range(y)) map("county", "iowa", fill = TRUE, col = gray(level)) title("Simulated Iowa Measurements") points(simIowa$lon, simIowa$lat) ## Map grid sites map("county", "iowa") title("Regular Grid of Coordinates") points(simGrid$lon, simGrid$lat)