I’m looking for ways to estimate quantiles with (1) splines, (2) penalization and (3) the ability to print an equation. RMS makes it easy to get (1) and (3), but I have not found a way to implement penalization:
library(dplyr) library(rms) set.seed(123) n <- 100 df <- data.frame(y = exp(x1 + rnorm(n)/4), x1 = rnorm(n)) dd <- datadist(df); options(datadist='dd') fq50 <- Rq(y ~ rcs(x1, 3), tau = 0.5, data = df) pred.q <- Function(fq50) sascode(pred.q)
I see that Roger Koenker’s original package on which
RMS::Rq() is based has a
method = "lasso" or
"scad" that “…implement the lasso penalty and Fan and Li smoothly clipped absolute deviation penalty, respectively. These methods should probably be regarded as experimental”.
In my application, I have 16 continuous predictors and n~3000.