Simulate residual multivariate t-distributed data from a polygenic model

Simulates residual multivariate t-distributed response data from a pedigree where the additive genetic, dominance genetic, and shared environmental effects are taken into account.

rmvt.pedigree(n = 1, pedigree, h2 = 0, c2 = 0, d2 = 0, df = 1)

Arguments

n

numeric. The number of simulations to generate

pedigree

a pedigree object

h2

numeric. The heritability

c2

numeric. The environmentability

d2

numeric. The dominance deviance effect

df

numeric. The degrees of freedom for the t distribution

Value

Returns a matrix with the simulated values with n columns (one for each simulation) and each row matches the corresponding individual from the pedigree

Details

The three parameters should have a sum: h2+c2+d2 that is less than 1. The total variance is set to 1, and the mean is zero.

See also

pedigree, kinship,

Author

Claus Ekstrom claus@rprimer.dk

Examples

library(kinship2)
library(mvtnorm)
mydata <- data.frame(id=1:5,
                     dadid=c(NA, NA, 1, 1, 1),
                     momid=c(NA, NA, 2, 2, 2),
                     sex=c("male", "female", "male", "male", "male"),
                     famid=c(1,1,1,1,1))
relation <- data.frame(id1=c(3), id2=c(4), famid=c(1), code=c(1))
ped <- pedigree(id=mydata$id, dadid=mydata$dadid, momid=mydata$momid,
                sex=mydata$sex, relation=relation)
rmvt.pedigree(2, ped, h2=.25, df=4)
#>            [,1]        [,2]
#> [1,]  0.5523797 -0.44705338
#> [2,] -1.1445881  2.17478573
#> [3,] -0.6015008  1.97148489
#> [4,]  0.3196021  0.57739408
#> [5,]  1.2754877 -0.03985478