GPD parameters prediction function for an EQRN_seq fitted object

Usage

EQRN_predict_params_seq(
  fit_eqrn,
  X,
  Y,
  intermediate_quantiles = NULL,
  return_parametrization = c("classical", "orthogonal"),
  interm_lvl = fit_eqrn$interm_lvl,
  seq_len = fit_eqrn$seq_len,
  device = default_device()
)

Arguments

fit_eqrn: Fitted "EQRN_seq" object.
X: Matrix of covariates to predict conditional GPD parameters.
Y: Response variable vector corresponding to the rows of X.
intermediate_quantiles: Vector of intermediate conditional quantiles at level fit_eqrn$interm_lvl.
return_parametrization: Which parametrization to return the parameters in, either "classical" or "orthogonal".
interm_lvl: Optional, checks that interm_lvl == fit_eqrn$interm_lvl.
seq_len: Data sequence length (i.e. number of past observations) used to predict each response quantile. By default, the training fit_eqrn$seq_len is used.
device: (optional) A torch::torch_device(). Defaults to default_device().

Value

Named list containing: "scales" and "shapes" as numerical vectors of length nrow(X), and the seq_len used.