emxRelatednessMatrix: Create a relatedness matrix
In jpritikin/emx: Easy Model-Builder Functions for 'OpenMx'

Description Usage Arguments Details Value See Also Examples

This function creates a relatedness matrix as an MxMatrix, often used in behavior genetics modeling.

1	emxRelatednessMatrix(nvar, values, labels, name='h')

`nvar`	numeric. The number of variables for the matrix, i.e. the number of rows or columns.
`values`	numeric vector. Values used in the matrix.
`labels`	character vector. Labels of the elements in the matrix. See Details.
`name`	character. The name of the matrix created.

The labels argument can be used to create a "definition variable" which populates the value from one of the data columns for each row in the data. In this context, if the genetic relatedness coefficient between a pair of individuals is given by a column in the data then that information can be used to create in the relatedness matrix. Alternatively, multiple groups can be created

An MxMatrix object.

emxGeneticFactorVariance

   
# Create a Cholesky variance matrix called 'A'
require(EasyMx)
ahmat <- emxRelatednessMatrix(2, c(1, .5, 1), labels=c(NA, 'data.RCoef', NA), name='AH')
# data.RCoef creates a definition variable and ignores the .5 value.