From deep@y@n@@@rk@r @ending from gm@il@com  Fri Oct  5 11:16:47 2018
From: deep@y@n@@@rk@r @ending from gm@il@com (Deepayan Sarkar)
Date: Fri, 5 Oct 2018 14:46:47 +0530
Subject: [Rd] 
 [R] Bug : Autocorrelation in sample drawn from stats::rnorm (hmh)
In-Reply-To: <5154ab19-d82c-ca24-676f-7eaeb03196f0@gmx.fr>
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Message-ID: <CADfFDC49X87yVfjVjBer3prLnuy5SaP-U+ekxiyHhBaY_RKvUw@mail.gmail.com>

On Fri, Oct 5, 2018 at 2:07 PM hmh <hugomh at gmx.fr> 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)
> should give on average the same output as
> sample(rnorm(N,0,1))

Agreed, but that is not what your code is testing. You seem to think
that something much more specific should be true; namely,

X[1:10] ~ iid normal, then

cor(X[1:9], X[2:10])

and

cor(sample(X[-1]), sample(X[-10]))

should have the same distribution. This is not at all obvious, and in
fact not true.

Please check the reference you have been pointed to. Here is a related
article in the same volume:

https://www.jstor.org/stable/2332719

-Deepayan


> Which is not the case. rnorm(N,0,1) should draw INDEPENDENT samples i.e.
> without time series structure !
>
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[Rd] [R] Bug : Autocorrelation in sample drawn from stats::rnorm (hmh)
Deepayan Sarkar