u <- runif (410)
u <- (u - min (u) ) / diff (range (u) )
constrained.sample <- function (rate)
{ plim <- pexp (c (9.6, 11.6), rate)
p <- plim [1] + diff (plim) * u
qexp (p, rate)
}
diff.sum <- function (rate)
sum (constrained.sample (rate) ) - 4200
rate <- uniroot (diff.sum, c (1, 2) )$root
q <- constrained.sample (rate)
length (q)
range (q)
sum (q)
On Wed, Jan 27, 2021 at 9:03 PM Denis Francisci
<denis.franci...@gmail.com> wrote:
>
> Hi,
> I would like to generate random numbers in R with some constraints:
> - my vector of numbers must contain 410 values;
> - min value must be 9.6 and max value must be 11.6;
> - sum of vector's values must be 4200.
> Is there a way to do this in R?
> And is it possible to generate this series in such a way that it follows a
> specific distribution form (for example exponential)?
> Thank you in advance,
>
> D.
>
> [[alternative HTML version deleted]]
>
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> and provide commented, minimal, self-contained, reproducible code.
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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