Maximum-likelihood GEV estimate

Usage

GEV_maxlik(
  Z,
  parametrization = c("classical", "return_level", "endpoint"),
  return_period = 100,
  orthogonal = FALSE,
  X = NULL,
  x_rlvl = NULL,
  loc_cols = NULL,
  scale_cols = NULL,
  shape_cols = NULL,
  out_param = parametrization,
  hessian = TRUE,
  maxit = 1e+06,
  method = c("Nelder-Mead", "BFGS", "CG", "L-BFGS-B", "SANN", "Brent"),
  ...
)

Arguments

Z: Block maxima observations.
parametrization: Likelihood parametrization. Alternatives to classical substitute for the location parameter.
return_period: Return period for the 'return_level' parametrization.
orthogonal: DEPRECATED.
X: Covariate matrix (for conditional/non-stationary fits).
x_rlvl: Covariate vector at which to reparametrize for the 'return_level' or 'endpoint' parametrizations (for conditional/non-stationary fits).
loc_cols: Column indices of X to use as covariate for the (conditional) location parameter (for conditional/non-stationary fits).
scale_cols: Column indices of X to use as covariate for the (conditional) scale parameter (for conditional/non-stationary fits).
shape_cols: Column indices of X to use as covariate for the (conditional) shape parameter (for conditional/non-stationary fits).
out_param: Additional output parametrization (same as parametrization, by default). If out_param != parametrization, the parameters are reparametrized from parametrization to out_param after estimation, in a separate output.
hessian: Logical. Should a numerically differentiated Hessian matrix be returned? See stats::optim() for more details.
maxit: The maximum number of iterations. See stats::optim() for more details.
method: The optimisation method to be used. See stats::optim() for more details.
...: Other arguments passed to the control argument of stats::optim().

Value

The fitted maximum-likelihood GEV as a GEV_ML object, containing:

mle: The estimated maximum likelihood GEV parameters, as a named vector (expressed in parametrization).
loglik: The log-likelihood of the estimated parameters, given the data
conv: Whether the optimisation procedure converged. See the convergence output of stats::optim() for more details.
hessian: The loglikelihood hessian evaluated at the estimated parameters, given the data.
parametrization: Likelihood parametrization.
out_mle: The estimated maximum likelihood GEV parameters, reparametrized in out_param.
out_parametrization: Additional output parametrization.