Is there a quantile function in R that includes both given x and given probs

Question

I need a R function that computes x values similarly to how the quantile function computes them while taking into account that the x values have already been computed using a quantile function.

I have a straightforward data frame with two columns, as seen in the following example:

probs x \s0.06 -120 \s0.1 -100 \s0.2 -97 \s0.24 -90 \s0.3 -80 \s0.5 -70 \s0.7 -60 \s0.89 -50 \s1 -40
(Although the data is more specific, this example will suffice.)

I don't have access to the original x data, however the x values were previously generated using a quantile function. Is there a function like the quantile function that calculates more quantiles between those numbers while still taking the weighting into account?

Answer 1

0
You should only perform a linear interpolation, in my opinion. For instance,

dat - structure(list(probs = c(0.06, 0.1, 0.2, 0.24, 0.3, 0.5, 0.7, 0.89, 1); x = c(-120, 100, 97, 90, 80, 70, -60, -50, -40)), class = "data.frame", row.names = c(NA, -9L))

c(0.1, 0.15, 0.2) #> fn - approxfun(dat$probs, dat$x) [1] -100.0 -98.5 -97.0