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 "flat" (default),
"normal" or "fixed" . |
beta |
hyper-parameter for the prior distribution of the mean (vector) parameter beta.
Only used if beta.prior = "normal" or beta.prior = "fixed" . For the latter beta defines the value of
the known mean. |
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 "uniform" (default),
"sc.inv.chisq" , "reciprocal" (gives improper posterior), or "fixed" . |
sigmasq |
fixed value of the parameter sigma^2 when
sigmasq.prior = "fixed" . Parameter S^2_{σ} in the scaled inverse-chi^2 prior distribution for sigma^2. |
df.sigmasq |
parameter n_{σ} in the scaled inverse-chi^2 prior distribution for sigma^2. |
phi.prior |
prior distribution for the range parameter phi.
Options are: "uniform" (propto 1),
"exponential" (exp(- nu * phi)),
"fixed" (known value of phi),
"squared.reciprocal" (1/phi^2),
"reciprocal" (1/phi).
Alternativelly, a user defined discrete distribution can be
specified by providing a vector of probabilities. These
probabilities corrresponds to a prior distribution with support phi.discrete . If the "fixed" the argument phi
should be provided and it is regarded as fixed when performing
predictions. |
phi |
fixed value of the parameter phi when
phi.prior = "fixed" . Mean of the prior distribution when phi.prior = "exponential" . |
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 tausq.rel = 0 . |
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
.