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GLmom (version 1.3.1)

set.prior: Set BMA prior distribution for candidate shape parameters

Description

Internal function that sets up the prior distribution for Bayesian Model Averaging (BMA) weights. Supports both normal and beta priors, with hyperparameters adapted based on the weighting method and L-moment estimate of xi.

Usage

set.prior(pen = NULL, numk = NULL, xi_lme = NULL, kpar = NULL, weight = NULL)

Value

A list containing:

prior

Numeric vector of prior probabilities (length numk)

prior_mu_std

(if pen="norm") Mean and std of the normal prior

p_q_beta

(if pen="beta") p and q parameters of the beta prior

Arguments

pen

Prior type: "norm" (normal) or "beta".

numk

Number of candidate submodels.

xi_lme

L-moment estimate of the shape parameter.

kpar

Numeric vector of candidate xi values.

weight

Weighting method name ("like", "gLd", or "med").