Exceedance probabilities P(risk > threshold)

Exceedance probabilities P(risk > threshold)

Usage

exceedance(object, thresholds, which = c("adjusted_rr", "relative_risk"))

Arguments

object

an "SDALGCP2_pred" object from predict.SDALGCP2.

thresholds

numeric vector of thresholds.

which

which quantity: "adjusted_rr" (the covariate-adjusted relative risk \(\exp(S)\), default) or "relative_risk" (the relative risk \(\exp(d'\beta + S)\)).

Value

a matrix of exceedance probabilities (locations x thresholds).

See also

map_exceedance to map them.

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")
## P(adjusted relative risk > 1) and > 1.5 for every region
ex <- exceedance(pr, thresholds = c(1, 1.5), which = "adjusted_rr")
head(ex)
#>           [,1]      [,2]
#> [1,] 0.4600000 0.1666667
#> [2,] 0.5400000 0.1600000
#> [3,] 0.3633333 0.0900000
#> [4,] 0.5633333 0.2533333
#> [5,] 0.9233333 0.6833333
#> [6,] 1.0000000 0.9866667
# }