Hi, I dont see from the solution pov they are different.
One followup Q though, how can I extend this to draw only integer mid-point between 0-100 while maintaining minimum difference as 5? Also, are all generated points are equally likely? Thanks for your time and suggestions. Thanks and regards, On Wed, 4 Jun 2025 at 17:13, Bert Gunter <bgunter.4...@gmail.com> wrote: > > Is Peter's solution different then: > > diffs <- cumsum(runif(9, 5, 100/9)) > x <-runif(1,0,100-diffs[9]) > c(x, x+diffs) > > I ask because: > 1. If yes, this is why more context is needed; > 2. If no, the above avoids a sort. > > Cheers, > Bert > > > > > On Tue, Jun 3, 2025 at 2:15 PM peter dalgaard <pda...@gmail.com> wrote: >> >> Can't you just generate 10 values in (0,55), sort them, generate the >> distances, add 5 and cumulate? >> >> > x <- sort(runif(10,0,55)) >> > d <- diff(x)+5 >> > cumsum(c(x[1],d)) >> [1] 12.27815 21.21060 26.37856 36.03812 41.97237 57.02945 67.86113 >> [8] 75.74085 81.28533 98.30792 >> >> >> > On 3 Jun 2025, at 09.21, Brian Smith <briansmith199...@gmail.com> wrote: >> > >> > Hi Richard, >> > >> > Thanks for your insight. >> > >> > As I mentioned in one of my earlier emails to the group, I imposed a >> > constraint of accuracy up to two decimal places in order to obtain a >> > finite set of possible values. For instance, if I were to round values >> > to zero decimal places, the number of unique sequences that could be >> > generated would be strictly finite and quite limited. Therefore, I >> > chose a precision of two decimal places to allow for a larger but >> > still finite number of possibilities. >> > >> > >> > Now, my question is: how can this accuracy constraint be imposed >> > effectively? >> > >> > Is the only practical method to generate samples, round each to two >> > decimal places, and then check for duplicates to ensure uniqueness? If >> > so, I’m concerned this might be inefficient, as many samples could be >> > discarded, making the process time-consuming. >> > >> > Is there a better or more efficient way to directly enforce this >> > constraint while generating the values? >> > >> > ________________________________ >> > >> > Additionally, could you please elaborate on your suggestion regarding >> > imposing minimum gap constraints by subtracting and then adding back >> > certain gaps? >> > >> > >> > For example, based on your earlier guidance, one possible sequence I >> > obtained is: >> > >> > >> > 10.07181, 14.49839, 14.74435, 18.75167, 42.70361, 55.79623, 63.40264, >> > 68.62261, 92.49899, 98.29308 >> > >> > >> > Now, I’d like to post-process this sequence to enforce a minimum >> > difference constraint of, say, 5 units between values (including both >> > lower and upper bounds). >> > >> > What would be the appropriate way to modify the sequence to impose >> > this kind of constraint? >> > >> > >> > Many thanks for your time and insight. >> > >> > On Tue, 3 Jun 2025 at 10:42, Richard O'Keefe <rao...@gmail.com> wrote: >> >> >> >> PS I forgot about the weird gaps requirement. >> >> What you do is subtract the gaps off and then add them back. I hope that >> >> is clear. >> >> >> >> On Sun, 1 Jun 2025 at 6:52 AM, Brian Smith <briansmith199...@gmail.com> >> >> wrote: >> >>> >> >>> Hi, >> >>> >> >>> Let say I have a range [0, 100] >> >>> >> >>> Now I need to simulate 1000 10 mid-points within the range with >> >>> accuracy upto second decimal number. >> >>> >> >>> Let say, one simulated set is >> >>> >> >>> X1, X2, ..., X10 >> >>> >> >>> Ofcourrse >> >>> >> >>> X1 < X2 < ... <X10 >> >>> >> >>> I have one more constraint that the difference between any 2 >> >>> consecutive mid-points shall be at-least 5.00. >> >>> >> >>> I wonder if there is any Statistical theory available to support this >> >>> kind of simulation. >> >>> >> >>> Alternately, is there any way in R to implement this? >> >>> >> >>> ______________________________________________ >> >>> 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. >> > >> > ______________________________________________ >> > 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. >> >> -- >> Peter Dalgaard, Professor, >> Center for Statistics, Copenhagen Business SchoolSolbjerg Plads 3, 2000 >> Frederiksberg, Denmark >> Phone: (+45)38153501 >> Office: A 4.23 >> Email: pd....@cbs.dk Priv: pda...@gmail.com >> >> ______________________________________________ >> 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. ______________________________________________ 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.
