Post-hoc monotonisation of estimated quantile curves (Chernozhukov,
Fernandez-Val and Galichon, 2010): at any covariate point, sorting the fitted
values across quantile levels into increasing order yields a valid,
non-crossing set of quantiles and never increases estimation error. This is
the v0.1 non-crossing strategy; joint constrained estimation is deferred.
Usage
rearrange_quantiles(preds)
Arguments
- preds
A numeric matrix of fitted quantiles with one column per
quantile level, ordered by increasing tau (rows = observations).
Value
A matrix of the same shape with each row sorted increasingly.
Examples
m <- rbind(c(1, 0.5, 2), c(0, 1, 0.8)) # some crossings
rearrange_quantiles(m)
#> [,1] [,2] [,3]
#> [1,] 0.5 1.0 2
#> [2,] 0.0 0.8 1