Subset coverage predictions — subset.imugap

Subsets predicted coverage draws by target metadata (variables), iterations, and chains.

Usage

# S3 method for class 'imugap_predict'
subset(x, subset, iteration, chain, ...)

Arguments

x: an object of class imugap_predict returned by [predict()].
subset: logical expression indicating which target variables to keep. Evaluated in the context of the target metadata [data.table()].
iteration: numeric, integer, or logical vector of iterations to keep.
chain: numeric, integer, or logical vector of chains to keep.
...: additional arguments (currently ignored).

Value

an object of class imugap_predict, subsetted with corresponding draws and target metadata.

Examples

# Load example prediction object
data("predict_sim", package = "imuGAP")

# Subset predictions by target metadata
subset(predict_sim, dose == 2)
#> An imuGAP predictions object (`imugap_predict`):
#>   Targets:   504 target population slices across 28 locations
#>   Posterior: 100 draws (4 chains x 25 iterations)
#> 
#> Use summary() to compute quantiles or as.data.frame() to convert to a long table.

# Subset predictions by iteration and chain
subset(predict_sim, iteration = 1:10, chain = 1)
#> An imuGAP predictions object (`imugap_predict`):
#>   Targets:   1008 target population slices across 28 locations
#>   Posterior: 10 draws (1 chain x 10 iterations)
#> 
#> Use summary() to compute quantiles or as.data.frame() to convert to a long table.