| fit.large {grmsem} | R Documentation |
Prefitted model: large data set
Description
A large quad-variate data set was simulated assuming an underlying Cholesky model, with 5000 observations per trait and high polygenicity (20,000 SNPs per genetic factor). Genetic trait variances were set to 0.30, 0.60, 0.60 and 0.70 respectively, and residual variances to 0.70, 0.40, 0.40 and 0.30. The data set is described in full, including genetic and residual covariances, in the vignette. A 4-variate Cholesky model was fitted to the data as described in the vignette and the output has been saved in fit.large.RData.
Usage
fit.large
Format
gsem.fit output (a list object)
- model.in
input parameters
- formula
fitted formula
- model.fit
optimisation output
- model.out
fitted gsem model
- VCOV
variance covariance matrix
- k
Number of phenotypes
- n
Number of observations across all phenotypes
- n.obs
Number of observations per phenotype
- n.ind
Number of individuals with at least one phenotype
- model
gsem model
- con
constraint
- ph.nms
phenotype names