Semi-conditional GPD MLEs and their train-validation likelihoods

Semi-conditional GPD MLEs and their train-validation likelihoods

Usage

semiconditional_train_valid_GPD_loss(
  Y_train,
  Y_valid,
  interm_quant_train,
  interm_quant_valid
)

Arguments

Y_train

Vector of "training" observations on which to estimate the MLEs.

Y_valid

Vector of "validation" observations, on which to estimate the out of training sample GPD loss.

interm_quant_train

Vector of intermediate quantiles serving as a varying threshold for each training observation.

interm_quant_valid

Vector of intermediate quantiles serving as a varying threshold for each validation observation.

Value

Named list containing:

• scaleGPD scale MLE inferred from the train set,

• shapeGPD shape MLE inferred from the train set,

• train_lossthe negative log-likelihoods of the MLEs over the training samples,

• valid_lossthe negative log-likelihoods of the MLEs over the validation samples.