Simulated aggregated disease-count data

A small, self-contained example dataset used throughout the help pages and vignettes. It is simulated from the model the package fits: an 8x8 lattice of regions, a spatially structured covariate, a latent Gaussian spatial field with exponential covariance, and Poisson counts with a population offset. The true fixed effects are (Intercept) = -6 and x1 = 0.6; the latent field has variance \(\sigma^2 = 0.3\) and exponential scale \(\phi = 4\).

Usage

sdalgcp_data

Format

An sf object of 64 POLYGON regions with columns:

region

integer region identifier (1-64).

cases

observed disease count in the region.

x1

a standardised, spatially structured covariate.

pop

population at risk (the offset; use offset(log(pop))).

geometry

the region polygon.

Source

Simulated; see data-raw/sdalgcp_data.R in the package sources.

See also

liver for a real disease-count example.

Examples

data(sdalgcp_data)
summary(sdalgcp_data$cases)
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#>   0.000   1.000   4.000   6.031  10.000  25.000 
plot(sdalgcp_data["cases"])