I note three problems with your data:
(1) The name "percent" is misleading, perhaps you want "probability"?
(2) There are straight (or near-straight) regions, each of which, is
equally (or near-equally) spaced, which is not what I would expect in
problems involving "quantiles".
(3) Your plot (approximating the distribution function) is
back-the-front (as per what is customary).
On Fri, Mar 5, 2021 at 10:14 PM PIKAL Petr <petr.pi...@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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