Map a fitted SDALGCP2 prediction

Maps any of the four predicted quantities from predict.SDALGCP2 – the relative risk "relative_risk", the covariate-adjusted relative risk "adjusted_rr", or their standard errors "relative_risk_se"/"adjusted_rr_se" – for either discrete (choropleth) or continuous (raster) predictions.

Usage

# S3 method for class 'SDALGCP2_pred'
plot(
  x,
  variable = c("relative_risk", "adjusted_rr", "relative_risk_se", "adjusted_rr_se"),
  bound = NULL,
  midpoint = NULL,
  title = NULL,
  ...
)

Arguments

x

an object of class "SDALGCP2_pred".

variable

one of "relative_risk", "adjusted_rr", "relative_risk_se", "adjusted_rr_se".

bound

optional sf boundary; continuous surfaces are masked to it and its outline overlaid.

midpoint

optional value to centre a diverging colour scale (defaults to 1 for the relative-risk columns, none for the standard errors).

title

optional plot title.

...

unused.

Value

a ggplot object.

Examples

# \donttest{
data(sdalgcp_data)
fit <- sdalgcp(cases ~ x1 + offset(log(pop)), data = sdalgcp_data,
               control = sdalgcp_control(n_sim = 2000, burnin = 500, thin = 5,
                                         reanchor = 0))
pr <- predict(fit, type = "discrete")
plot(pr, variable = "relative_risk")          # choropleth of relative risk

plot(pr, variable = "adjusted_rr_se")         # its uncertainty

# }