The function generates increasing amount of errors to the pedigree structure and calculates heritability for each simulation. For each level of the error proportion, a number of simulation equal to B are repeated. Errors are generated by replacing fathers with the most similar individual from the same generation.
simul.replace.similar.herit(pedigree, lambda, B, data,
model, prior, nitt, thin, burnin)
A dataset containing the initial pedigree structure. It must have three columns: id, parent1, parent2.
A vector of real numbers specifying the error proportion to be generated.
An integer specifying the number of simulations to be run for each error level.
A dataset containing the phenotypic measurements on the population and the covariates which are included in the model. The trait shoul be named differently than 'trait' (see MCMCglmm)
A object of class MCMCglmm used to calculate heritability.
Prior distribution for MCMCglmm model
Number of iterations for MCMCglmm model
Thinning interval for MCMCglmm model
Burn in period for MCMCglmm model
A list:
A dataset containing all the simulated values for heritability
A dataset containing all the simulated standard errors for heritability
A dataset containing all the simulated values for additive variance
A dataset containing all the simulated values for environmental variance