Tail excess probability prediction method using an EQRN_iid object

Usage

# S3 method for class 'EQRN_seq'
excess_probability(object, ...)

Arguments

object

Fitted "EQRN_seq" object.

...

Arguments passed on to EQRN_excess_probability_seq

val: Quantile value(s) used to estimate the conditional excess probability or cdf.
X: Matrix of covariates to predict the response's conditional excess probabilities.
Y: Response variable vector corresponding to the rows of X.
intermediate_quantiles: Vector of intermediate conditional quantiles at level fit_eqrn$interm_lvl.
interm_lvl: Optional, checks that interm_lvl == fit_eqrn$interm_lvl.
crop_predictions: Whether to crop out the fist seq_len observations (which are NA) from the returned vector
body_proba: Value to use when the predicted conditional probability is below interm_lvl (in which case it cannot be precisely assessed by the model). If "default" is given (the default), paste0(">",1-interm_lvl) is used if proba_type=="excess", and paste0("<",interm_lvl) is used if proba_type=="cdf".
proba_type: Whether to return the "excess" probability over val (default) or the "cdf" at val.
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

Vector of probabilities (and possibly a few body_proba values if val is not large enough) of length nrow(X) (or nrow(X)-seq_len if crop_predictions).

Details

See EQRN_excess_probability_seq() for more details.