sim_reference_pop: Simulate Reference Population with Pigmentation Traits

In mispitools: Missing Person Identification Tools

Simulate Reference Population with Pigmentation Traits

Description

Generates a simulated population dataset with correlated pigmentation characteristics (hair color, skin color, eye color). The traits are simulated using conditional probability distributions that reflect realistic correlations between these characteristics.

Usage

sim_reference_pop(n = 1000, seed = 1234)

Arguments

n	Integer. Number of individuals to simulate. Default: 1000.
seed	Integer. Random seed for reproducibility. Default: 1234.

Details

Hair color categories:

1. Blonde/Light

2. Light brown

3. Medium brown

4. Dark brown

5. Black

The simulation uses conditional probability distributions where:

• Hair color is sampled first from population frequencies

• Skin color is sampled conditional on hair color

• Eye color is sampled conditional on both hair and skin color

This captures realistic correlations (e.g., darker hair tends to co-occur with darker skin and eyes).

Value

A data.frame with three columns:

• hair_colour: Hair color category (1-5)

• skin_colour: Skin color category (1-5)

• eye_colour: Eye color category (1-5)

Categories are numbered 1 (lightest) to 5 (darkest).

References

Marsico FL, et al. (2023). "Likelihood ratios for non-genetic evidence in missing person cases." Forensic Science International: Genetics, 66, 102891. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.fsigen.2023.102891")}

See Also

compute_conditioned_prop for computing proportions, compute_reference_prop for reference frequencies, lr_pigmentation for pigmentation LR calculations.

Examples

# Simulate a population of 500 individuals
pop_data <- sim_reference_pop(n = 500, seed = 123)
head(pop_data)

# Check trait distributions
table(pop_data$hair_colour)
table(pop_data$skin_colour)
table(pop_data$eye_colour)

# Use for LR calculations
conditioned <- compute_conditioned_prop(pop_data, h = 1, s = 1, y = 1,
                                        eh = 0.01, es = 0.01, ey = 0.01)
unconditioned <- compute_reference_prop(pop_data)

mispitools documentation built on Aug. 26, 2026, 1:08 a.m.