Combines node values across specified grouping variables using different aggregation methods. The aggregation method can be specified via agg_func parameter:
"prob": Combined probability assuming independence
"sum": Sum of values
"avg": Average of values
NULL: defaults to "sum" if mc_name ends in "_n", else defaults to "prob"
Usage
agg_totals(
mcmodule,
mc_name,
agg_keys = NULL,
agg_suffix = NULL,
prefix = NULL,
name = NULL,
summary = TRUE,
keep_variates = FALSE,
agg_func = NULL
)Arguments
- mcmodule
mcmodule object containing nodes and data
- mc_name
name of node to aggregate
- agg_keys
grouping variables for aggregation
- agg_suffix
Suffix for aggregated node name (default: "agg")
- prefix
Optional prefix for output node name - includes metadata as add_prefix() (default: NULL)
- name
Custom name for output node (optional)
- summary
whether to include summary statistics (default: TRUE)
- keep_variates
whether to preserve individual values (default: FALSE)
- agg_func
aggregation method ("prob", "sum", "avg", or NULL)
Examples
imports_mcmodule <- agg_totals(
imports_mcmodule, "no_detect_a",
agg_keys = c("scenario_id", "pathogen")
)
#> 3 variates per group for no_detect_a
print(imports_mcmodule$node_list$no_detect_a_agg$summary)
#> mc_name scenario_id pathogen mean sd Min 2.5%
#> 1 no_detect_a_agg 0 a 0.3264681 0.01416266 0.2891882 0.2996985
#> 4 no_detect_a_agg 0 b 0.6610791 0.03083952 0.5904521 0.6087351
#> 25% 50% 75% 97.5% Max nsv Na's
#> 1 0.3160279 0.3266146 0.3365067 0.3530371 0.3632177 1001 0
#> 4 0.6354902 0.6612333 0.6865692 0.7119438 0.7183356 1001 0