quantile_to_interval: Transform from a quantile format to an interval format

In epiforecasts/scoringutils: Utilities for Scoring and Assessing Predictions

Transform from a quantile format to an interval format

Description

Quantile format In a quantile format, a prediction is characterised by one or multiple predicted values and the corresponding quantile levels. For example, a prediction in a quantile format could be represented by the 0.05, 0.25, 0.5, 0.75 and 0.95 quantiles of the predictive distribution.

Interval format In the interval format, two quantiles are assumed to form a prediction interval. Prediction intervals need to be symmetric around the median and are characterised by a lower and an upper bound. The lower bound is defined by the lower quantile and the upper bound is defined by the upper quantile. A 90% prediction interval, for example, covers 90% of the probability mass and is defined by the 5% and 95% quantiles. A forecast could therefore be characterised by one or multiple prediction intervals, e.g. the lower and upper bounds of the 50% and 90% prediction intervals (corresponding to the 0.25 and 0.75 as well as the 0.05 and 0.095 quantiles).

Usage

quantile_to_interval(...)

## S3 method for class 'data.frame'
quantile_to_interval(forecast, format = "long", keep_quantile_col = FALSE, ...)

## S3 method for class 'numeric'
quantile_to_interval(observed, predicted, quantile_level, ...)

Arguments

...	Arguments
forecast	A data.table with forecasts in a quantile-based format (see as_forecast()).
format	The format of the output. Either "long" or "wide". If "long" (the default), there will be a column boundary (with values either "upper" or "lower" and a column interval_range that contains the range of the interval. If "wide", there will be a column interval_range and two columns lower and upper that contain the lower and upper bounds of the prediction interval, respectively.
keep_quantile_col	keep the quantile_level column in the final output after transformation (default is FALSE). This only works if format = "long". If format = "wide", the quantile_level column will always be dropped.
observed	Numeric vector of size n with the observed values.
predicted	Numeric nxN matrix of predictive quantiles, n (number of rows) being the number of forecasts (corresponding to the number of observed values) 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	Vector of of size N with the quantile levels for which predictions were made.

Value

A data.table with forecasts in an interval format.

quantile_to_interval.data.frame: a data.table in an interval format (either "long" or "wide"), with or without a quantile_level column. Rows will not be reordered.

quantile_to_interval.numeric: a data.table in a wide interval format with columns forecast_id, observed, lower, upper, and interval_range. The forecast_id column is a unique identifier for each forecast. Rows will be reordered according to forecast_id and interval_range.

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