sim_poi_prelim: Simulate Preliminary Investigation Data for Persons of...

In mispitools: Missing Person Identification Tools

Simulate Preliminary Investigation Data for Persons of Interest

Description

Generates a simulated database of preliminary investigation data for persons of interest (POIs) or unidentified human remains (UHRs). Supports two case types: missing children and missing migrants.

Usage

sim_poi_prelim(
  casetype = "children",
  dateinit = "1975/01/01",
  scenario = 1,
  femaleprop = 0.5,
  ext = 100,
  numsims = 10000,
  seed = 123,
  birthprob = c(0.09, 0.9, 0.01),
  region = c("North America", "South America", "Africa", "Asia", "Europe", "Oceania"),
  regionprob = c(0.2, 0.2, 0.2, 0.1, 0.2, 0.1)
)

Arguments

casetype	Character. Type of missing person case: "children": Generates birth date, sex, birth type, and region "migrants": Generates age, sex, height, and region Default: "children".
dateinit	Character. Minimum birth date for simulated POIs in "YYYY/MM/DD" format. Only used for casetype = "children". Default: "1975/01/01".
scenario	Integer (1 or 2). Birth date distribution scenario: 1: Non-uniform (gamma distribution, more realistic) 2: Uniform distribution Only used for casetype = "children". Default: 1.
femaleprop	Numeric (0-1). Proportion of females in the simulated population. Default: 0.5.
ext	Numeric. Extension parameter: Scenario 1: Scale factor for gamma distribution Scenario 2: Number of days range Default: 100.
numsims	Integer. Number of POIs/UHRs to simulate. Default: 10000.
seed	Integer. Random seed for reproducibility. Default: 123.
birthprob	Numeric vector of length 3. Probabilities for birth type: c(home_birth, hospital_birth, unknown/adoption). Only for "children". Default: c(0.09, 0.9, 0.01).
region	Character vector. Names of regions/locations. Default: c("North America", "South America", "Africa", "Asia", "Europe", "Oceania").
regionprob	Numeric vector. Probabilities for each region. Must sum to 1 and have same length as region. Default: c(0.2, 0.2, 0.2, 0.1, 0.2, 0.1).

Details

For missing children cases, this function simulates characteristics of children who may have been taken during periods of conflict or human rights violations, with their identity documents potentially falsified.

For missing migrants cases, this simulates characteristics of unidentified human remains that may correspond to missing migrants.

The birth date distribution in scenario 1 uses a gamma distribution with shape=12, which creates a more realistic non-uniform pattern of births.

Value

A data.frame with columns depending on casetype:

• children: POI-ID, DBD (declared birth date), Sex, Birth-type, Region

• migrants: UHR-ID, Age, Sex, Height, Region

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

sim_mp_prelim for simulating missing person data, sim_lr_prelim for using this data in LR calculations.

Examples

# Simulate children case database
db_children <- sim_poi_prelim(
  casetype = "children",
  dateinit = "1975/01/01",
  scenario = 1,
  numsims = 100,
  seed = 123
)
head(db_children)

# Simulate migrants case database
db_migrants <- sim_poi_prelim(
  casetype = "migrants",
  numsims = 100,
  seed = 456
)
head(db_migrants)
summary(db_migrants$Age)

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