Calculates probabilities and expected counts across hierarchical levels (trial, subset, set) in a structured population. Uses trial probabilities and handles nested sampling with conditional probabilities.
Usage
trial_totals(
mcmodule,
mc_names,
trials_n,
subsets_n = NULL,
subsets_p = NULL,
name = NULL,
prefix = NULL,
combine_prob = TRUE,
all_suffix = NULL,
level_suffix = c(trial = "trial", subset = "subset", set = "set"),
mctable = set_mctable(),
agg_keys = NULL,
agg_suffix = NULL,
keep_variates = FALSE,
summary = TRUE
)Arguments
- mcmodule
mcmodule object containing input data and node structure
- mc_names
Vector of node names to process
- trials_n
Trial count column name
- subsets_n
Subset count column name (optional)
- subsets_p
Subset prevalence column name (optional)
- name
Custom name for output nodes (optional)
- prefix
Prefix for output node names (optional)
- combine_prob
Combine probability of all nodes assuming independence (default: TRUE)
- all_suffix
Suffix for combined node name (default: "all")
- level_suffix
A list of suffixes for each hierarchical level (default: c(trial="trial",subset="subset",set="set"))
- mctable
Data frame containing Monte Carlo nodes definitions (default: set_mctable())
- agg_keys
Column names for aggregation (optional)
- agg_suffix
Suffix for aggregated node names (default: "hag")
- keep_variates
whether to preserve individual values (default: FALSE)
- summary
Include summary statistics if TRUE (default: TRUE)
Value
Updated mcmodule object containing:
Combined node probabilities
Probabilities and counts at trial level
Probabilities and counts at subset level
Probabilities and counts at set level
Examples
imports_mcmodule <- trial_totals(
mcmodule = imports_mcmodule,
mc_names = "no_detect_a",
trials_n = "animals_n",
subsets_n = "farms_n",
subsets_p = "h_prev",
mctable = imports_mctable
)
#> data_name is not equal for all nodes, using 'no_detect_a' data_name 'imports_data' for node creation
print(imports_mcmodule$node_list$no_detect_a_set$summary)
#> mc_name pathogen origin mean sd Min 2.5%
#> 1 no_detect_a_set a nord 0.3764715 0.020323487 0.3411145 0.3427513
#> 2 no_detect_a_set a south 0.2982527 0.062479652 0.1830303 0.1913597
#> 3 no_detect_a_set a east 0.6035354 0.046265356 0.5219547 0.5262205
#> 4 no_detect_a_set b nord 0.9875522 0.008374908 0.9687340 0.9701970
#> 5 no_detect_a_set b south 0.9587261 0.008070145 0.9437208 0.9445872
#> 6 no_detect_a_set b east 0.9664391 0.020728570 0.9181797 0.9221154
#> 25% 50% 75% 97.5% Max nsv Na's
#> 1 0.3583955 0.3767396 0.3945887 0.4078370 0.4095042 1001 0
#> 2 0.2463023 0.2981711 0.3519906 0.3966782 0.4012021 1001 0
#> 3 0.5640380 0.6049379 0.6449311 0.6758179 0.6794182 1001 0
#> 4 0.9815032 0.9899148 0.9947579 0.9973527 0.9975547 1001 0
#> 5 0.9519542 0.9589960 0.9658775 0.9711185 0.9717524 1001 0
#> 6 0.9504834 0.9716804 0.9840396 0.9916738 0.9920768 1001 0