quantile from quantile table calculation without original data
Your example could probably be resolved with approx. If you want a more robust solution, it looks like the fBasics package can do spline interpolation. You may want to spline on the log of your size variable and use exp on the output if you want to avoid negative results.
On March 5, 2021 1:14:22 AM PST, PIKAL Petr <petr.pikal at precheza.cz> wrote:
Dear all
I have table of quantiles, probably from lognormal distribution
dput(temp)
temp <- structure(list(size = c(1.6, 0.9466, 0.8062, 0.6477, 0.5069,
0.3781, 0.3047, 0.2681, 0.1907), percent = c(0.01, 0.05, 0.1,
0.25, 0.5, 0.75, 0.9, 0.95, 0.99)), .Names = c("size", "percent"
), row.names = c(NA, -9L), class = "data.frame")
and I need to calculate quantile for size 0.1
plot(temp$size, temp$percent, pch=19, xlim=c(0,2))
ss <- approxfun(temp$size, temp$percent)
points((0:100)/50, ss((0:100)/50))
abline(v=.1)
If I had original data it would be quite easy with ecdf/quantile
function but without it I am lost what function I could use for such
task.
Please, give me some hint where to look.
Best regards
Petr
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