prior.glm.control {geoRglm} | R Documentation |
This auxiliary function defines prior options for
pois.krige.bayes
and binom.krige.bayes
.
prior.glm.control(beta.prior = c("flat", "normal", "fixed"), beta = NULL, beta.var.std = NULL, sigmasq.prior = c("uniform", "sc.inv.chisq", "reciprocal", "fixed"), sigmasq = NULL, df.sigmasq = NULL, phi.prior = c("uniform", "exponential","fixed", "squared.reciprocal", "reciprocal"), phi = NULL, phi.discrete = NULL, tausq.rel = 0)
beta.prior |
prior distribution for the mean (vector) parameter beta. The options are |
beta |
hyper-parameter for the prior distribution of the mean (vector) parameter beta.
Only used if |
beta.var.std |
standardised (co)variance hyperparameter(s) for the prior for the mean (vector) parameter beta. The (co)variance matrix for beta is given by the multiplication of this matrix by sigma^2. Only used if 'beta.prior = "normal"'. |
sigmasq.prior |
prior distribution for the parameter sigma^2. The options are |
sigmasq |
fixed value of the parameter sigma^2 when
|
df.sigmasq |
parameter in the scaled inverse-chi^2 prior distribution for sigma^2. |
phi.prior |
prior distribution for the range parameter phi.
Options are: |
phi |
fixed value of the parameter phi when
|
phi.discrete |
support points for the discretisation of the prior for the parameter phi. |
tausq.rel |
the value of the relative nugget parameter
tau_R^2. Default is |
A list with processed arguments to be passed to the main function.
Ole F. Christensen OleF.Christensen@agrsci.dk,
Paulo J. Ribeiro Jr. Paulo.Ribeiro@est.ufpr.br.
pois.krige.bayes
and binom.krige.bayes
.