Description Usage Arguments Details Value Author(s) See Also Examples

This function computes the parameter "Psi" which relates the additive genetic variance on the latent scale to the additive genetic variance on the observed scale: Va.obs = (Psi^2) * Va

1 |

`mu` |
Latent intercept estimated from a GLMM (set to 0 if |

`var` |
Latent total phenotypic variance estimated from a GLMM. Usually, the sum of the estimated variances of the random effects, plus the "residual" variance. (numeric of length 1) |

`d.link.inv` |
Derivative of the inverse-link function. (function) |

`predict` |
Optional vector of predicted values on the latent scale (i.e. matrix product |

`width` |
Parameter for the integral computation. The integral is evaluated from |

The parameter "Psi" is the average of the derivative of the inverse-link function. The additive genetic variance on the observed scale is linked to the additive genetic variance on the latent scale by : Va.obs = (Psi^2) * Va.lat.

This function yields the "Psi" parameter. (numeric)

Pierre de Villemereuil & Michael B. Morrissey

`QGmvpsi`

, `QGparams`

, `QGpred`

, `QGlink.funcs`

, `QGmean`

, `QGvar.dist`

, `QGvar.exp`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
## Example using binom1.probit model
mu <- 0
va <- 1
vp <- 2
# The inverse-link for a probit is the CDF of a standard Gaussian
# Hence its derivative is the PDF of a standard Gaussian
dinv <- function(x){dnorm(x)}
# Computing Psi
Psi <- QGpsi(mu = 0, var = 2, d.link.inv = dinv)
# Computing additive variance on the observed scale
(Psi^2) * va
# This function is used by QGparams to obtain var.a.obs
QGparams(mu = 0, var.p = vp, var.a = va, model = "binom1.probit")
# Same results as above!
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.