Description Details Author(s) References

Compute various quantitative genetics parameters from a Generalised Linear Mixed Model (GLMM) estimates. Especially, it yields the observed phenotypic mean, phenotypic variance and additive genetic variance.

The DESCRIPTION file:
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This package gives the values on the observed scale for several quantitative genetics parameter using estimates from a Generalised Linear Mixed Model (GLMM). If a fitness function is assumed or measured, it also predicts the evolutionary response to selection on the observed scale.

The two main functions of this package are `QGparams`

and `QGpred`

. The first allows to compute the quantitative genetics parameters on the observed scale for any given GLMM and its estimates. The second allows to compute a predicted response to evolution on the observed scale using GLMM estimates and an assumed/measured/inferred fitness function.

For some distribution/link models (e.g. Binomial/probit and Poisson and Negative Binomial with logartihm or square-root link), a closed form solutions of the integrals computed by this package are available. They are automatially used by `QGparams`

and this function only.

Pierre de Villemereuil <[email protected]>

Maintainer: Pierre de Villemereuil <[email protected]>

de Villemereuil, P., Schielzeth, H., Nakagawa, S., and Morrissey, M.B. (2016). General methods for evolutionary quantitative genetic inference from generalised mixed models. Genetics 204, 1281-1294.

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