prior.glm.control {geoRglm}R Documentation

Defines prior options

Description

This auxiliary function defines prior options for pois.krige.bayes and binom.krige.bayes.

Usage

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)

Arguments

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.

Value

A list with processed arguments to be passed to the main function.

Author(s)

Ole F. Christensen OleF.Christensen@agrsci.dk,
Paulo J. Ribeiro Jr. Paulo.Ribeiro@est.ufpr.br.

See Also

pois.krige.bayes and binom.krige.bayes.


[Package geoRglm version 0.8-24 Index]