Aggregates node values across grouping variables using various methods (combined probability, sum, mean, or automatic selection). Returns an updated mcmodule with a new aggregated node.
Usage
agg_variates(
mcmodule,
mc_name,
agg_keys = NULL,
agg_suffix = NULL,
prefix = NULL,
name = NULL,
summary = TRUE,
keep_variates = FALSE,
agg_func = NULL
)Arguments
- mcmodule
An
mcmoduleobject. Module containing node list and data.- mc_name
Character. Name of node to aggregate.
- agg_keys
Character vector, optional. Column names for grouping. If
NULL, defaults to"scenario_id". Default:NULL.- agg_suffix
Character, optional. Suffix for aggregated node name. Default:
NULL.- prefix
Character, optional. Prefix for output node name. Default:
NULL.- name
Character, optional. Custom name for output node. Default:
NULL.- summary
Logical. If
TRUE, include summary statistics. Default:TRUE.- keep_variates
Logical. If
TRUE, preserve individual variate values. Default:FALSE.- agg_func
Character, optional. Aggregation method:
"prob"for combined probability,"sum","avg", orNULLfor automatic selection. Default:NULL.
Details
If sample-design nodes are aggregated, the resulting node will be equal
to the original node, but with the "agg_total" type and summary statistics
added.
Examples
imports_mcmodule <- agg_variates(
imports_mcmodule, "no_detect",
agg_keys = c("scenario_id", "pathogen")
)
#> 3 variates per group for no_detect
print(imports_mcmodule$node_list$no_detect_agg$summary)
#> mc_name scenario_id pathogen mean sd Min 2.5%
#> 1 no_detect_agg 0 a 0.3264284 0.01433595 0.2895656 0.2999061
#> 4 no_detect_agg 0 b 0.6587557 0.03139364 0.5953081 0.6054365
#> 25% 50% 75% 97.5% Max nsv Na's
#> 1 0.3162902 0.3263546 0.3372695 0.3534805 0.3607581 1001 0
#> 4 0.6328318 0.6586071 0.6847111 0.7103067 0.7193540 1001 0