Predict relative risk from an sdalgcp fit

Returns a prediction object carrying, for every location, the posterior mean and standard error of the relative risk relative_risk (\(\exp(\eta)=\exp(d'\beta+S)\)) and the covariate-adjusted relative risk adjusted_rr (\(\exp(S)\)). Map it with plot() and get hotspot probabilities with exceedance.

Usage

# S3 method for class 'sdalgcp'
predict(
  object,
  type = c("discrete", "continuous"),
  sampler = c("mcmc", "laplace"),
  cellsize = NULL,
  ...
)

Arguments

object

an "sdalgcp" fit.

type

"discrete" (region level, default) or "continuous" (a grid surface). Ignored for spatio-temporal fits.

sampler

"mcmc" (default) or "laplace".

cellsize

grid spacing for type = "continuous".

...

passed to the underlying predictor.

Value

for a spatial fit, an sf of class "SDALGCP2_pred" with relative_risk, relative_risk_se, adjusted_rr and adjusted_rr_se columns (polygons for type = "discrete", grid points for "continuous"); for a spatio-temporal fit, an "SDALGCP2_ST_pred" object (see predict.SDALGCP2_ST).

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)            # discrete by default; an sf of relative risks
head(pr)
#> Simple feature collection with 6 features and 8 fields
#> Geometry type: POLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 0 ymin: 0 xmax: 15 ymax: 2.5
#> CRS:           NA
#>   region cases          x1  pop                       geometry relative_risk
#> 1      1     2 -2.03331626 3840 POLYGON ((0 0, 2.5 0, 2.5 2...  0.0005317242
#> 2      2     3 -1.64601792 3985 POLYGON ((2.5 0, 5 0, 5 2.5...  0.0007289839
#> 3      3     1 -1.25871959 2236 POLYGON ((5 0, 7.5 0, 7.5 2...  0.0008197207
#> 4      4     0 -0.87142125  846 POLYGON ((7.5 0, 10 0, 10 2...  0.0012181931
#> 5      5     3 -0.48412292  874 POLYGON ((10 0, 12.5 0, 12....  0.0025647230
#> 6      6    12 -0.09682458 2231 POLYGON ((12.5 0, 15 0, 15 ...  0.0046964955
#>   relative_risk_se adjusted_rr adjusted_rr_se
#> 1     0.0002366949   0.9517023      0.4236464
#> 2     0.0003048683   1.0135720      0.4238859
#> 3     0.0003512447   0.8853696      0.3793747
#> 4     0.0005202427   1.0221081      0.4365024
#> 5     0.0010285486   1.6716415      0.6703899
#> 6     0.0012838339   2.3779273      0.6500302
# }