[R] random numbers with constraints

[Abby Spurdle]

I note that there's a possibility of floating point errors.
If all values have one digit after the decimal point, you could replace:
qexp (p, rate) with round (qexp (p, rate), 1).

However, sometimes uniroot will fail, due to problems with input.

On Thu, Jan 28, 2021 at 5:02 AM Denis Francisci
<denis.francisci using gmail.com> wrote:
>
> Wonderful!
> This is exactly what I need!
> Thank you very much!!
>
> Denis
>
>
>
> Il giorno mer 27 gen 2021 alle ore 10:58 Abby Spurdle <spurdle.a using gmail.com> ha scritto:
>>
>> 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.francisci using 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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