Map a spatio-temporal prediction for one time

Maps a chosen quantity ("relative_risk", "adjusted_rr", "relative_risk_se", "adjusted_rr_se" or "exceedance") for a selected time slice of a spatio-temporal prediction.

Usage

# S3 method for class 'SDALGCP2_ST_pred'
plot(
  x,
  time = attr(x, "times")[1],
  what = c("relative_risk", "adjusted_rr", "relative_risk_se", "adjusted_rr_se",
    "exceedance"),
  threshold = 1,
  which = c("adjusted_rr", "relative_risk"),
  ...
)

Arguments

x

an "SDALGCP2_ST_pred" object from predict() on an "SDALGCP2_ST" fit.

time

the time to map (one of the fitted times); defaults to the first. Use NULL to facet all times.

what

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

threshold

threshold for what = "exceedance".

which

for exceedance: "adjusted_rr" (default) or "relative_risk".

...

unused.

Value

a ggplot object.

Examples

# \donttest{
data(sdalgcp_data)
times <- 1:3
panel <- do.call(rbind, lapply(times, function(t) {
  d <- sdalgcp_data; d$time <- t
  d$cases <- rpois(nrow(d), d$pop * exp(-6 + 0.6 * d$x1 + 0.1 * (t - 2)))
  d
}))
fit <- sdalgcp(cases ~ x1 + offset(log(pop)), data = panel, time = "time",
               control = sdalgcp_control(n_sim = 2000, burnin = 500, thin = 5,
                                         reanchor = 0))
pr <- predict(fit)
plot(pr, time = 2)                 # one time slice

plot(pr, time = NULL)              # facet all times

plot(pr, what = "exceedance", threshold = 1.2, time = 3)

# }