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.
set.prior(pen = NULL, numk = NULL, xi_lme = NULL, kpar = NULL, weight = NULL)A list containing:
Numeric vector of prior probabilities (length numk)
(if pen="norm") Mean and std of the normal prior
(if pen="beta") p and q parameters of the beta prior
Prior type: "norm" (normal) or "beta".
Number of candidate submodels.
L-moment estimate of the shape parameter.
Numeric vector of candidate xi values.
Weighting method name ("like", "gLd", or "med").