Assert that inputs are correct for quantile-based forecast — assert_input

Function assesses whether the inputs correspond to the requirements for scoring quantile-based forecasts.

Usage

assert_input_quantile(
  observed,
  predicted,
  quantile_level,
  unique_quantile_levels = TRUE
)

observed: Input to be checked. Should be a numeric vector with the observed values of size n.
predicted: Input to be checked. Should be nxN matrix of predictive quantiles, n (number of rows) being the number of data points and N (number of columns) the number of quantiles per forecast. If observed is just a single number, then predicted can just be a vector of size N.
quantile_level: Input to be checked. Should be a vector of size N that denotes the quantile levels corresponding to the columns of the prediction matrix.
unique_quantile_levels: Whether the quantile levels are required to be unique (TRUE, the default) or not (FALSE).

Returns NULL invisibly if the assertion was successful and throws an error otherwise.