excess_probability.EQRN_seq: Tail excess probability prediction method using an EQRN_iid...

In EQRN: Extreme Quantile Regression Neural Networks for Risk Forecasting

Tail excess probability prediction method using an EQRN_iid object

Description

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().

Details

See EQRN_excess_probability_seq() for more details.

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).

EQRN documentation built on April 4, 2025, 12:45 a.m.