R: Estimate Quantitative Genetics Parameters from Generalised Linear Mixed Models

# Estimate Quantitative Genetics Parameters from Generalised Linear Mixed Models

## Documentation for package ‘QGglmm’ version 0.8.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

QGglmm-package | Estimate Quantitative Genetics Parameters from Generalised Linear Mixed Models
QGglmm | Estimate Quantitative Genetics Parameters from Generalised Linear Mixed Models
QGicc | Intra - Class Correlation coefficients (ICC) on the observed data scale
QGlink.funcs | List of functions according to a distribution and a link function
QGmean | Compute the phenotypic mean on the observed scale
QGmvicc | Intra - Class Correlation coefficients (ICC) on the observed data scale (multivariate analysis).
QGmvmean | Compute the multivariate phenotypic mean on the observed scale
QGmvparams | Quantitative Genetics parameters from GLMM estimates (multivariate analysis).
QGmvpred | Predict the evolutionary response to selection on the observed scale
QGmvpsi | Compute a multivariate "Psi" (used to compute the additive genetic variance on the observed scale).
QGparams | Quantitative Genetics parameters from GLMM estimates.
QGpred | Predict the evolutionary response to selection on the observed scale
QGpsi | Compute "Psi" (used to compute the additive genetic variance on the observed scale).
QGvar.dist | Compute the distribution variance
QGvar.exp | Compute the variance of expected values (i.e. the latent values after inverse-link transformation.)
QGvcov | Compute the phenotypic variance-covariance matrix on the observed / expected scale