weight.com: Compute model averaging weights

Description

Internal function that computes weights for model averaging across K candidate GEV submodels. Supports multiple weighting schemes including likelihood-based, generalized L-moment distance, and median-based methods. Optionally includes BMA prior integration.

Usage

weight.com(
  data = NULL,
  numk = NULL,
  hosking = NULL,
  kpar = NULL,
  numom = 3,
  xqa = NULL,
  varcom = TRUE,
  boot.lme = TRUE,
  cov.lme = NULL,
  surr = FALSE,
  type = "full",
  trim = NULL,
  cov.type = "ratio",
  bma = TRUE,
  pen = "norm"
)

Value

A list containing:

weight: Weighting method name
numk: Number of submodels
wtgd: MA weight vector (length numk)
bmaw: BMA weight vector (length numk)
zp: Quantile matrix (numq x numk)
kpar: Candidate xi values
prob.call: Submodel fitting results
xzp: Surrogate quantile matrix (if surr=TRUE)

Arguments

data: Numeric vector of data.
numk: Number of candidate submodels.
hosking: List containing LME results, MLE, and bootstrap information.
kpar: Numeric vector of candidate xi values.
numom: Number of L-moments to use (default 3).
xqa: Probability vector for surrogate model fitting.
varcom: Logical. Whether to compute variance components (default TRUE).
boot.lme: Logical. Whether bootstrap LME was performed (default TRUE).
cov.lme: Pre-computed LME covariance (default NULL).
surr: Logical. Whether to compute surrogate quantiles (default FALSE).
type: Type of computation: "full" (default).
trim: Left trimming level for L-moments.
cov.type: Covariance type: "ratio" or "lambda" (default "ratio").
bma: Logical. Whether to compute BMA weights (default TRUE).
pen: BMA prior type: "norm" or "beta" (default "norm").