assert_input_quantile: Assert that inputs are correct for quantile-based forecast

In epiforecasts/scoringutils: Utilities for Scoring and Assessing Predictions

Assert that inputs are correct for quantile-based forecast

Description

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
)

Arguments

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).

Value

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

epiforecasts/scoringutils documentation built on April 23, 2024, 4:56 p.m.