validate_individual_data: Validate individual data for hierarchical models

In fb4package: 'Fish Bioenergetics 4.0' Model Implementation with High-Performance 'TMB' Backend

Validate individual data for hierarchical models

Description

Validates individual fish data for hierarchical mark-recapture models.

Usage

validate_individual_data(
  individual_data,
  require_positive_growth = TRUE,
  check_outliers = TRUE
)

Arguments

individual_data	Data frame with individual observations
require_positive_growth	Whether growth must be positive
check_outliers	Whether to check for outliers

Value

Invisibly returns TRUE if all checks pass. Throws an error if individual_data is not a data frame, if required columns (individual_id, initial_weight, final_weight) are missing, if weights are non-positive, or if growth is negative when require_positive_growth = TRUE. Issues warnings for outlier observations when check_outliers = TRUE.

Examples

ind <- data.frame(individual_id = c("A", "B"),
                  initial_weight = c(50, 80),
                  final_weight   = c(120, 180))
isTRUE(validate_individual_data(ind))

fb4package documentation built on May 8, 2026, 1:07 a.m.