Nope.
This IS a bug:
_*The negative auto-correlation mostly disappear when I randomize small
samples using the R function '*__*sample*__*'.*_
Please check thoroughly the code of the 1st mail I sent, there should be
no difference between the two R functions I wrote to illustrate the bug.
I got it !
thanks and sorry for annoying you with that.
have a nice day,
hugo
On 05/10/2018 11:16, Deepayan Sarkar wrote:
> On Fri, Oct 5, 2018 at 2:07 PM hmh wrote:
>> On 05/10/2018 10:28, Annaert Jan wrote:
>>> you discard any time series structure;
>> But that is PRECISELY what a call a
On Fri, Oct 5, 2018 at 2:07 PM hmh wrote:
>
> On 05/10/2018 10:28, Annaert Jan wrote:
> > you discard any time series structure;
> But that is PRECISELY what a call a bug:
> There should not be any "time series structure" in the output or rnorm,
> runif and so on but there is one.
>
> rnorm(N,0,1)
On 05/10/2018 10:28, Annaert Jan wrote:
> you discard any time series structure;
But that is PRECISELY what a call a bug:
There should not be any "time series structure" in the output or rnorm,
runif and so on but there is one.
rnorm(N,0,1)
should give on average the same output as
sample(rnorm(N
On 05/10/2018, 09:45, "R-help on behalf of hmh" wrote:
Hi,
Thanks William for this fast answer, and sorry for sending the 1st mail
to r-help instead to r-devel.
I noticed that bug while I was simulating many small random walks using
c(0,cumsum(rnorm(10))). The
Hi,
Thanks William for this fast answer, and sorry for sending the 1st mail
to r-help instead to r-devel.
I noticed that bug while I was simulating many small random walks using
c(0,cumsum(rnorm(10))). Then the negative auto-correlation was inducing
a muchsmaller space visited by the random w
Hi Hugo,
I've been able to replicate your bug, including for other distributions (runif,
rexp, rgamma, etc) which shouldn't be surprising since they're probably all
drawing from the same pseudo-random number generator. Interestingly, it does
not seem to depend on the choice of seed, I am not su
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