log_shift: Log transformation with an additive shift

View source: R/transform-forecasts.R

log_shiftR Documentation

Log transformation with an additive shift

Description

Function that shifts a value by some offset and then applies the natural logarithm to it.

Usage

log_shift(x, offset = 0, base = exp(1))

Arguments

x

vector of input values to be transformed

offset

Number to add to the input value before taking the natural logarithm.

base

A positive number: the base with respect to which logarithms are computed. Defaults to e = exp(1).

Details

The output is computed as log(x + offset)

Value

A numeric vector with transformed values

References

Transformation of forecasts for evaluating predictive performance in an epidemiological context Nikos I. Bosse, Sam Abbott, Anne Cori, Edwin van Leeuwen, Johannes Bracher, Sebastian Funk medRxiv 2023.01.23.23284722 \Sexpr[results=rd]{tools:::Rd_expr_doi("https://doi.org/10.1101/2023.01.23.23284722")} https://www.medrxiv.org/content/10.1101/2023.01.23.23284722v1 # nolint

Examples

library(magrittr) # pipe operator
log_shift(1:10)
log_shift(0:9, offset = 1)

example_quantile[observed > 0, ] %>%
  as_forecast_quantile() %>%
  transform_forecasts(fun = log_shift, offset = 1)

epiforecasts/scoringutils documentation built on Dec. 11, 2024, 11:12 a.m.