# ibdBootstrap: Bootstrap estimation of IBD coefficients In forrel: Forensic Pedigree Analysis and Relatedness Inference

 ibdBootstrap R Documentation

## Bootstrap estimation of IBD coefficients

### Description

This function produces (parametric or nonparametric) bootstrap estimates of the IBD coefficients between two individuals. Both kappa and delta coefficients are supported (see `ibdEstimate()`).

### Usage

```ibdBootstrap(
x = NULL,
ids = NULL,
param = NULL,
kappa = NULL,
delta = NULL,
N,
method = "parametric",
freqList = NULL,
plot = TRUE,
seed = NULL
)
```

### Arguments

 `x` A `ped` object. If `method = "parametric"`, this is only used to extract the allele frequencies, and can be skipped if `freqList` is provided. `ids` A pair of ID labels. `param` Either NULL (default), "kappa" or "delta". (See below.) `kappa, delta` Probability vectors of length 3 (kappa) or 9 (delta). Exactly one of `param`, `kappa` and `delta` must be non-NULL. If `kappa` and `delta` are both NULL, the appropriate set of coefficients is computed as `ibdEstimate(x, ids, param)`. `N` The number of simulations. `method` Either "parametric" (default) or "nonparametric". Abbreviations are allowed. see Details for more information about each method. `freqList` A list of probability vectors: The allele frequencies for each marker. `plot` A logical, only relevant for bootstraps of kappa. If TRUE, the bootstrap estimates are plotted in the IBD triangle. `seed` An integer seed for the random number generator (optional).

### Details

The parameter `method` controls how bootstrap estimates are obtained in each replication.

If `method = "parametric"`, new profiles for two individuals are simulated from the input coefficients, followed by a re-estimation of the coefficients.

If `method = "nonparametric"`, the original markers are sampled with replacement, before the coefficients are re-estimated.

### Value

A data frame with `N` rows containing the bootstrap estimates. The last column (`dist`) gives the euclidean distance to the original coefficients, viewed as a point in R^3 (kappa) or R^9 (delta).

`ibdEstimate()`

### Examples

```
# Frequency list of 15 standard STR markers
freqList = NorwegianFrequencies[1:15]

# Number of bootstrap simulations (increase!)
N = 5

# Bootstrap estimates for kappa of full siblings
boot1 = ibdBootstrap(kappa = c(0.25, .5, .25), N = N, freqList = freqList)
boot1

# Mean deviation
mean(boot1\$dist)

# Same, but with the 9 identity coefficients.
delta = c(0, 0, 0, 0, 0, 0, .25, .5, .25)
boot2 = ibdBootstrap(delta = delta, N = N, freqList = freqList)

# Mean deviation
mean(boot2\$dist)

#### Non-parametric bootstrap.
# Requires `x` and `ids` to be provided

x = nuclearPed(2)
x = markerSim(x, ids = 3:4, N = 50, alleles = 1:10, seed = 123)

bootNP = ibdBootstrap(x, ids = 3:4, param = "kappa", method = "non", N = N)

# Parametric bootstrap can also be done with this syntax
bootP = ibdBootstrap(x, ids = 3:4, param = "kappa", method = "par", N = N)

```

forrel documentation built on March 18, 2022, 5:19 p.m.