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BMAmevt (version 1.0.5)

prior.pb: Prior parameter distribution for the Pairwise Beta model

Description

Density and generating function of the prior distribution.

Usage

prior.pb(type = c("r", "d"), n, par, Hpar, log, dimData)

Value

Either a matrix with n rows containing a random parameter sample generated under the prior (if type == "d"), or the (log)-density of the parameter par.

Arguments

type

One of the character strings "r", "d"

n

The number of parameters to be generated. Only used if type == "r".

par

A vector with positive components: The parameter where the density is to be taken. Only used if type=="d". In the Pairwise Beta model, par is of length choose(p,2)+1. The first element is the global dependence parameter, the subsequent ones are the pairwise dependence parameters, in lexicographic order (e.g. \(\beta_{1,2}, \beta_{1,3}, \beta_{2,3}\).

Hpar

list of Hyper-parameters : see pb.Hpar for a template.

log

logical. Should the density be returned on the log scale ? Only used if type=="d"

dimData

The dimension of the sample space. (one more than the dimension of the simplex)

Author

Anne Sabourin

Details

The parameters components are independent, log-normal.