fb4package (version 2.0.0)

analyze_feeding_performance: Analyze feeding performance from FB4 results

Description

Analyzes feeding-related metrics including consumption rates, feeding efficiency, and p_value estimates with uncertainty.

Usage

analyze_feeding_performance(
  result,
  individual_id = NULL,
  confidence_level = 0.95
)

Value

A named list with at minimum method (character),

has_uncertainty (logical), and individual_id. Additional elements present when the relevant data are available:

total_consumption

The list returned by get_consumption_uncertainty (estimate, se, ci_lower, ci_upper, plus context scalars).

daily_consumption

Sub-list (estimate, se, ci_lower, ci_upper) for the daily consumption rate (g/day).

specific_consumption

Sub-list (same four slots) for the specific consumption rate (g consumption / g fish / day).

p_value

Structure depends on method: for hierarchical it contains population_mean, population_se, population_sd, and n_individuals; for single-individual methods it contains estimate, se, ci_lower, and ci_upper.

feeding_efficiency

Sub-list (estimate, se, ci_lower, ci_upper) for the ratio of total growth to total consumption (dimensionless).

Arguments

result

FB4 result object

individual_id

Individual ID for hierarchical models (NULL for population/single individual)

confidence_level

Confidence level for intervals (default 0.95)

Examples

# \donttest{
data(fish4_parameters)
sp   <- fish4_parameters[["Oncorhynchus tshawytscha"]]$life_stages$adult
info <- fish4_parameters[["Oncorhynchus tshawytscha"]]$species_info
bio  <- Bioenergetic(
  species_params     = sp,
  species_info       = info,
  environmental_data = list(
    temperature = data.frame(Day = 1:30, Temperature = rep(12, 30))
  ),
  diet_data = list(
    proportions = data.frame(Day = 1:30, Prey1 = 1.0),
    energies    = data.frame(Day = 1:30, Prey1 = 5000),
    prey_names  = "Prey1"
  ),
  simulation_settings = list(initial_weight = 100, duration = 30)
)
bio$species_params$predator$ED_ini <- 5000
bio$species_params$predator$ED_end <- 5500
result <- run_fb4(bio, strategy = "direct", p_value = 0.5, verbose = FALSE)
feeding <- analyze_feeding_performance(result)
# }