unconditional_train_valid_GPD_loss: Unconditional GPD MLEs and their train-validation likelihoods
In EQRN: Extreme Quantile Regression Neural Networks for Risk Forecasting

unconditional_train_valid_GPD_loss

R Documentation

Unconditional GPD MLEs and their train-validation likelihoods

Unconditional GPD MLEs and their train-validation likelihoods

unconditional_train_valid_GPD_loss(Y_train, interm_lvl, Y_valid)

`Y_train`	Vector of "training" observations on which to estimate the MLEs.
`interm_lvl`	Probability level at which the empirical quantile should be used as the threshold.
`Y_valid`	Vector of "validation" observations, on which to estimate the out of training sample GPD loss.

Named list containing:

`scale`	GPD scale MLE inferred from the train set,
`shape`	GPD shape MLE inferred from the train set,
`train_loss`	the negative log-likelihoods of the MLEs over the training samples,
`valid_loss`	the negative log-likelihoods of the MLEs over the validation samples.