Hi Rui,
Thanks for the explanation.
But in this case, are we looking at the correct solution at all?
My goal is to generate random vector where:
1) the first element is bounded by (a[1], b[1]) and second element is
bounded by (a[2], b[2])
2) sum of the element is s
According to the outcome,
The first matrix values are bounded by c(a[1], b[1]) & second matrix
values are bounded by c(a[2], b[2])
But,
regarding the sum, I think we should have sum (element-wise) sum
should be equal to s = 0.05528650577311.
How could we achieve that then?
On Tue, 22 Apr 2025 at 22:03, Rui Barradas <ruipbarra...@sapo.pt> wrote:
>
> Às 12:39 de 22/04/2025, Brian Smith escreveu:
> > Hi Rui,
> >
> > Many thanks for your time and insight.
> >
> > However, I am not sure if I could understand the code. Below is what I
> > tried based on your code
> >
> > library(Surrogate)
> > a <- c(0.015, 0.005)
> > b <- c(0.070, 0.045)
> > set.seed(2025)
> > res <- mapply(\(a, b, s, n, m) RandVec(a, b, s, n, m),
> > MoreArgs = list(s = 0.05528650577311, n = 2, m = 10000), a,
> > b)
> >
> > res1 = res[[1]]
> > res2 = res[[2]]
> >
> > apply(res1, 1, min) > a ## [1] TRUE TRUE
> > apply(res2, 1, min) > a ## [1] FALSE TRUE
> >
> > I could not understand what basically 2 blocks of res signify? Which
> > one I should take as final simulation of the vector? If I take the
> > first block then the lower bound condition is fulfilled, but not with
> > the second block. However with the both blocks, the total equals s is
> > satisfying.
> >
> > I appreciate your further insight.
> >
> > Thanks and regards,
> >
> > On Mon, 21 Apr 2025 at 20:43, Rui Barradas <ruipbarra...@sapo.pt> wrote:
> >>
> >> Hello,
> >>
> >> Inline.
> >>
> >> Às 16:08 de 21/04/2025, Rui Barradas escreveu:
> >>> Às 15:27 de 21/04/2025, Brian Smith escreveu:
> >>>> Hi,
> >>>>
> >>>> There is a function called RandVec in the package Surrogate which can
> >>>> generate andom vectors (continuous number) with a fixed sum
> >>>>
> >>>> The help page of this function states that:
> >>>>
> >>>> a
> >>>>
> >>>> The function RandVec generates an n by m matrix x. Each of the m
> >>>> columns contain n random values lying in the interval [a,b]. The
> >>>> argument a specifies the lower limit of the interval. Default 0.
> >>>>
> >>>> b
> >>>>
> >>>> The argument b specifies the upper limit of the interval. Default 1.
> >>>>
> >>>> However in my case, the lower and upper limits are not same. For
> >>>> example, if I need to draw a pair of number x, y, such that x + y = 1,
> >>>> then the lower and upper limits are different.
> >>>>
> >>>> I tried with below code
> >>>>
> >>>> library(Surrogate)
> >>>>
> >>>> RandVec(a=c(0.1, 0.2), b=c(0.2, 0.8), s=1, n=2, m=5)$RandVecOutput
> >>>>
> >>>> This generates error with message
> >>>>
> >>>> Error in if (b - a == 0) { : the condition has length > 1
> >>>>
> >>>> Is there any way to generate the numbers with different lower and
> >>>> upper limits?
> >>>>
> >>>> ______________________________________________
> >>>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> >>>> https://stat.ethz.ch/mailman/listinfo/r-help
> >>>> PLEASE do read the posting guide https://www.R-project.org/posting-
> >>>> guide.html
> >>>> and provide commented, minimal, self-contained, reproducible code.
> >>> Hello,
> >>>
> >>> Use ?mapply to cycle through all values of a and b.
> >>> Note that the output matrices are transposed, the random vectors are the
> >>> rows.
> >> Sorry, this is not true. The columns are the random vectors, as
> >> documented. An example setting the RNG seed, for reproducibility.
> >>
> >>
> >> library(Surrogate)
> >>
> >> a <- c(0.1, 0.2)
> >> b <- c(0.2, 0.8)
> >> set.seed(2025)
> >> res <- mapply(\(a, b, s, n, m) RandVec(a, b, s, n, m),
> >> MoreArgs = list(s = 1, n = 2, m = 5), a, b)
> >>
> >> res
> >> #> $RandVecOutput
> >> #> [,1] [,2] [,3] [,4] [,5]
> >> #> [1,] 0.146079 0.1649319 0.1413759 0.257086 0.1715478
> >> #> [2,] 0.253921 0.2350681 0.2586241 0.142914 0.2284522
> >> #>
> >> #> $RandVecOutput
> >> #> [,1] [,2] [,3] [,4] [,5]
> >> #> [1,] 0.5930918 0.2154583 0.6915523 0.7167089 0.3617918
> >> #> [2,] 0.4069082 0.7845417 0.3084477 0.2832911 0.6382082
> >>
> >> lapply(res, colSums)
> >> #> $RandVecOutput
> >> #> [1] 0.4 0.4 0.4 0.4 0.4
> >> #>
> >> #> $RandVecOutput
> >> #> [1] 1 1 1 1 1
> >>
> >>
> >> Hope this helps,
> >>
> >> Rui Barradas
> >>>
> >>>
> >>> library(Surrogate)
> >>>
> >>> a <- c(0.1, 0.2)
> >>> b <- c(0.2, 0.8)
> >>> mapply(\(a, b, s, n, m) RandVec(a, b, s, n, m),
> >>> MoreArgs = list(s = 1, n = 2, m = 5), a, b)
> >>> #> $RandVecOutput
> >>> #> [,1] [,2] [,3] [,4] [,5]
> >>> #> [1,] 0.2004363 0.1552328 0.2391742 0.1744857 0.1949236
> >>> #> [2,] 0.1995637 0.2447672 0.1608258 0.2255143 0.2050764
> >>> #>
> >>> #> $RandVecOutput
> >>> #> [,1] [,2] [,3] [,4] [,5]
> >>> #> [1,] 0.2157416 0.4691191 0.5067447 0.7749258 0.7728955
> >>> #> [2,] 0.7842584 0.5308809 0.4932553 0.2250742 0.2271045
> >>>
> >>>
> >>> Hope this helps,
> >>>
> >>> Rui Barradas
> >>>
> >>>
> >>
> >>
> >> --
> >> Este e-mail foi analisado pelo software antivírus AVG para verificar a
> >> presença de vírus.
> >> www.avg.com
> Hello,
>
> The two blocks of res are the two random matrices, one for each
> combination of (a,b). mapply passes each of the values in its arguments
> list (the ellipses in the help page) and computes the anonymous function
> with the pairs (a[1], b[1]), (a[2], b[2]).
>
> Since a and b are two elements vectors the output res is a two members
> named list. Your error is to compare the result of apply(res2, 1, min)
> to a, when you should compare to a[2]. See the code below.
>
>
> library(Surrogate)
> a <- c(0.015, 0.005)
> b <- c(0.070, 0.045)
> set.seed(2025)
> res <- mapply(\(a, b, s, n, m) RandVec(a, b, s, n, m),
> MoreArgs = list(s = 0.05528650577311, n = 2, m = 10000),
> a, b)
>
> res1 = res[[1]]
> res2 = res[[2]]
>
> # first check that the sums are correct
> # these sums should be s = 0.05528650577311, up to floating-point accuracy
> lapply(res, \(x) colSums(x[, 1:5]) |> print(digits = 14L))
> #> [1] 0.05528650577311 0.05528650577311 0.05528650577311 0.05528650577311
> #> [5] 0.05528650577311
> #> [1] 0.05528650577311 0.05528650577311 0.05528650577311 0.05528650577311
> #> [5] 0.05528650577311
> #> $RandVecOutput
> #> [1] 0.05528651 0.05528651 0.05528651 0.05528651 0.05528651
> #>
> #> $RandVecOutput
> #> [1] 0.05528651 0.05528651 0.05528651 0.05528651 0.05528651
>
> # now check the min and max
> apply(res1, 1, min) > a[1L] ## [1] TRUE TRUE
> #> [1] TRUE TRUE
> apply(res2, 1, min) > a[2L] ## [1] TRUE TRUE
> #> [1] TRUE TRUE
>
> apply(res1, 1, max) < b[1L] ## [1] TRUE TRUE
> #> [1] TRUE TRUE
> apply(res2, 1, max) < b[2L] ## [1] TRUE TRUE
> #> [1] TRUE TRUE
>
>
>
> Which one should you take as final simulation of the vector? Both.
> The first matrix values are bounded by c(a[1], b[1]) with column sums
> equal to s.
> The second matrix values are bounded by c(a[2], b[2]) with column sums
> also equal to s.
>
> Hoep this helps,
>
> Rui Barradas
>
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