multilevel_MSE: Multilevel quantile MSEs
In EQRN: Extreme Quantile Regression Neural Networks for Risk Forecasting

multilevel_MSE

R Documentation

Multilevel quantile MSEs

Description

Multilevel version of mean_squared_error().

Usage

multilevel_MSE(
  True_Q,
  Pred_Q,
  proba_levels,
  prefix = "",
  na.rm = FALSE,
  give_names = TRUE,
  sd = FALSE
)

Arguments

`True_Q`	Matrix of size `n_obs` times `proba_levels`, whose columns are the vectors of ground-truths at each `proba_levels` and each row corresponds to an observation or realisation.
`Pred_Q`	Matrix of the same size as `True_Q`, whose columns are the predictions at each `proba_levels` and each row corresponds to an observation or realisation.
`proba_levels`	Vector of probability levels at which the predictions were made. Must be of length `ncol(Pred_Q)`.
`prefix`	A string prefix to add to the output's names (if `give_names` is `TRUE`).
`na.rm`	A logical value indicating whether `NA` values should be stripped before the computation proceeds.
`give_names`	Whether to name the output MSEs (bool).
`sd`	Whether to return the squared error standard deviation (bool).

Value

A vector of length length(proba_levels) giving the mean square errors between each respective columns of True_Q and Pred_Q. If give_names is TRUE, the output vector is named paste0(prefix, "MSE_q", proba_levels). If sd==TRUE a named list is instead returned, containing the "MSEs" described above and "SDs", their standard deviations.