View source: R/missingPersonIP.R
missingPersonIP | R Documentation |
This function simulates the LR distribution for the true missing person in a reference family. The output contains both the total and marker-wise LR of each simulation, as well as various summary statistics. If a specific LR threshold is given, the inclusion power is computed as the probability that LR exceeds the threshold.
missingPersonIP(
reference,
missing,
markers,
nsim = 1,
threshold = NULL,
disableMutations = NA,
seed = NULL,
verbose = TRUE
)
reference |
A |
missing |
The ID label of the missing pedigree member. |
markers |
A vector indicating the names or indices of markers attached
to the source pedigree. If NULL (default), then all markers attached to the
source pedigree are used. If |
nsim |
A positive integer: the number of simulations |
threshold |
A numeric vector with one or more positive numbers used as the likelihood ratio thresholds for inclusion |
disableMutations |
This parameter determines how mutation models are treated. Possible values are as follows:
|
seed |
An integer seed for the random number generator (optional). |
verbose |
A logical. |
A mpIP
object, which is essentially a list with the following
entries:
LRperSim
: A numeric vector of length nsim
containing the total LR for
each simulation.
meanLRperMarker
: The mean LR per marker, over all simulations.
meanLR
: The mean total LR over all simulations.
meanLogLR
: The mean total log10(LR)
over all simulations.
IP
: A named numeric of the same length as threshold
. For each element
of threshold
, the fraction of simulations resulting in a LR exceeding the
given number.
time
: The total computation time.
params
: A list containing the input parameters missing
, markers
,
nsim
, threshold
and disableMutations
# Four siblings; the fourth is missing
x = nuclearPed(4)
# Remaining sibs typed with 5 triallelic markers
x = markerSim(x, N = 5, ids = 3:5, alleles = 1:3, seed = 123, verbose = FALSE)
# Compute inclusion power statistics
ip = missingPersonIP(x, missing = 6, nsim = 5, threshold = c(10, 100))
ip
# LRs from each simulation
ip$LRperSim
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