makeDsim: Creates the dominance genetic relationship matrix through...
In nadiv: Functions to construct non-additive genetic relatedness matrices

Description Usage Arguments Details Value Note Author(s) References See Also Examples

Given a pedigree, the matrix of coefficients of fraternity are returned - the D matrix - as well as a simulated set of coefficients of fraternity (Ovaskainen et al. 2008).

1	makeDsim(pedigree, N, invertD = FALSE, calcSE = FALSE)

`pedigree`	A pedigree with columns organized: ID, Dam, Sire
`N`	The number of times to simulate genotypes for the pedigree
`invertD`	A logical indicating whether or not to invert the D matrix
`calcSE`	A logical indicating whether or not the standard errors for each coefficient of fraternity should be calculated

Missing parents (e.g., base population) should be denoted by either 'NA' or '0'.

Ovaskainen et al. (2008) indicated that the method of calculating the D matrix (see makeD) is only an approximation. They proposed a simulation method that is implemented here. This should be more appropriate when inbreeding occurs in the pedigree.

The value, listDsim will list both the approximate values (returned from makeD) as well as the simulated values. If calcSE is TRUE, these values will be listed in listDsim.

`A`	the A matrix in sparse matrix form
`D`	the approximate D matrix in sparse matrix form
`logDetD`	the log determinant of the approximate D matrix
`Dinv`	the inverse of the approximate D matrix in sparse matrix form
`listDinv`	the three column form of the non-zero elements for the inverse of the approximate D matrix
`Dsim`	the simulated D matrix in sparse matrix form
`logDetDsim`	the log determinant of the simulated D matrix
`Dsiminv`	the inverse of the simulated D matrix in sparse matrix form
`listDsim`	the three column form of the non-zero and non-self elements for the simulated D matrix
`listDsiminv`	the three column form of the non-zero elements for the inverse of the simulated D matrix

This simulation can take a long time for large values of N. If unsure, it is advisable to start with a lower N and gradually increase to gain a sense of the time required to execute a desired N.

matthewwolak@gmail.com

Ovaskainen, O., Cano, J.M., & Merila, J. 2008. A Bayesian framework for comparative quantitative genetics. Proceedings of the Royal Society B 275, 669-678.

makeD