Displaying 7 results from an estimated 7 matches for "499748".
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49.748
2018 Sep 20
5
Bias in R's random integers?
...nned to integrate such an unbiased sampling scheme into the dqrng
package, which I have now started. [2]
Using Duncan's example, the results look much better:
> library(dqrng)
> m <- (2/5)*2^32
> y <- dqsample(m, 1000000, replace = TRUE)
> table(y %% 2)
0 1
500252 499748
Currently I am taking the other interpretation of "truncated":
> table(dqsample(2.5, 1000000, replace = TRUE))
0 1
499894 500106
I will adjust this to whatever is decided for base R.
However, there is currently neither long vector nor weighted sampling
support. And the...
2018 Sep 20
4
Bias in R's random integers?
...[2]
> >
> > Using Duncan's example, the results look much better:
> >> library(dqrng)
> >> m <- (2/5)*2^32
> >> y <- dqsample(m, 1000000, replace = TRUE)
> >> table(y %% 2)
> >>
> > 0 1
> >
> > 500252 499748
>
> Another useful diagnostic is
>
> plot(density(y[y %% 2 == 0]))
>
> Obviously that should give a more or less uniform density, but for
> values near m, the default sample() gives some nice pretty pictures of
> quite non-uniform densities.
>
> By the way, ther...
2011 Feb 15
1
outbound call leg CALLID
Hello everyone
Is there a possibility to catch an outbound callleg ID for the follovong
scenario: some carrier -----> ------(asterisk1) --->-----asterisk2 ?
I can get inbound callid for asterisk1 with a ${SIPCALLID} in
extensions.conf or to look it up in cdrs field (are the same). But how about
outbound? I have all calls just forwarded through asterisk1, not answered
and for every call I
2018 Sep 20
0
Bias in R's random integers?
...nto the dqrng
> package, which I have now started. [2]
>
> Using Duncan's example, the results look much better:
>
>> library(dqrng)
>> m <- (2/5)*2^32
>> y <- dqsample(m, 1000000, replace = TRUE)
>> table(y %% 2)
>
> 0 1
> 500252 499748
Another useful diagnostic is
plot(density(y[y %% 2 == 0]))
Obviously that should give a more or less uniform density, but for
values near m, the default sample() gives some nice pretty pictures of
quite non-uniform densities.
By the way, there are actually quite a few examples of very larg...
2018 Sep 21
0
Bias in R's random integers?
...9;s example, the results look much better:
> > >> library(dqrng)
> > >> m <- (2/5)*2^32
> > >> y <- dqsample(m, 1000000, replace = TRUE)
> > >> table(y %% 2)
> > >>
> > > 0 1
> > >
> > > 500252 499748
> >
> > Another useful diagnostic is
> >
> > plot(density(y[y %% 2 == 0]))
> >
> > Obviously that should give a more or less uniform density, but for
> > values near m, the default sample() gives some nice pretty pictures of
> > quite non-unifor...
2018 Sep 21
3
Bias in R's random integers?
...he results look much better:
>>>>> library(dqrng)
>>>>> m <- (2/5)*2^32
>>>>> y <- dqsample(m, 1000000, replace = TRUE)
>>>>> table(y %% 2)
>>>>>
>>>> 0 1
>>>>
>>>> 500252 499748
>>>
>>> Another useful diagnostic is
>>>
>>> plot(density(y[y %% 2 == 0]))
>>>
>>> Obviously that should give a more or less uniform density, but for
>>> values near m, the default sample() gives some nice pretty pictures of
>>...
2018 Sep 19
2
Bias in R's random integers?
A quick point of order here: arguing with Duncan in this forum is
helpful to expose ideas, but probably neither side will convince the
other; eventually, if you want this adopted in core R, you'll need to
convince an R-core member to pursue this fix.
In the meantime, a good, well-tested implementation in a
user-contributed package (presumably written in C for speed) would be
enormously