Maximum Likelihood Estimate (Fisherian) — fisher

Creates a fisher_mle object representing a maximum likelihood estimate with methods for standard inference. This class emphasizes the Fisherian approach to likelihood-based inference.

fisher_mle(
  par,
  vcov = NULL,
  loglik_val,
  hessian = NULL,
  score_val = NULL,
  nobs = NULL,
  converged = TRUE,
  optim_result = NULL
)

Arguments

par: Numeric vector of parameter estimates (may be named)
vcov: Variance-covariance matrix of the estimates
loglik_val: Log-likelihood value at the MLE
hessian: Hessian matrix of the log-likelihood at the MLE
score_val: Optional score vector at the MLE (should be near zero)
nobs: Number of observations used in estimation
converged: Logical indicating if optimization converged
optim_result: Raw result from optim() for diagnostics

Value

An object of class c("fisher_mle", "mle")