[R] Simulating mid-points from a defined range

[Brian Smith]

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.4567 using 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 <pdalgd using 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 <briansmith199312 using 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 <raoknz using 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 <briansmith199312 using 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 using 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 using 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.mes using cbs.dk  Priv: PDalgd using gmail.com
>>
>> ______________________________________________
>> R-help using 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.