GPD tensor loss function for training a EQRN network

GPD tensor loss function for training a EQRN network

Usage

loss_GPD_tensor(
  out,
  y,
  orthogonal_gpd = TRUE,
  shape_penalty = 0,
  prior_shape = NULL,
  return_agg = c("mean", "sum", "vector", "nanmean", "nansum")
)

Arguments

out

Batch tensor of GPD parameters output by the network.

y

Batch tensor of corresponding response variable.

orthogonal_gpd

Whether the network is supposed to regress in the orthogonal reparametrization of the GPD parameters (recommended).

shape_penalty

Penalty parameter for the shape estimate, to potentially regularize its variation from the fixed prior estimate.

prior_shape

Prior estimate for the shape, used only if shape_penalty>0.

return_agg

The return aggregation of the computed loss over the batch. Must be one of "mean", "sum", "vector", "nanmean", "nansum".

Value

The GPD loss over the batch between the network output ans the observed responses as a torch::Tensor, whose dimensions depend on return_agg.