Re: [Boost-users] [Boost.Random] Discrete distribution behavior

Subject: Re: [Boost-users] [Boost.Random] Discrete distribution behavior
From: sguazt (marco.guazzone_at_[hidden])
Date: 2012-06-05 04:26:32

On Tue, Jun 5, 2012 at 9:51 AM, sguazt <marco.guazzone_at_[hidden]> wrote:
> On Tue, Jun 5, 2012 at 7:57 AM, Steven Watanabe <watanabesj_at_[hidden]> wrote:
>> AMDG
>>
> Thanks Steven!
>
> [cut]
>
>> The algorithm generates a table
>> that looks like this:
>>
>> std::vector<std::pair<double, int> > table = {
>>  { 0.3, 1 },
>>  { 0.5, 2 },
>>  { 1.0, 0 }
>> };
>>
>> Then the generation algorithm is
>>
>> double x = uniform_01<>(engine);
>> int result = uniform_int<>(0, 2)(engine);
>> if (x < table[result].first) return result;
>> else return table[result].second;
>>
>
>
> Sorry, I didn't have enough background knowledge on this topic.
>
> My error was to relate the U(0,1) x number to a CDF value.
> Anyway I performed a Monte-Carlo simulation and the results (the
> empirical PDF) match with the original PDF.
>
> Since I still don't understand how event weights are preserved and I
> don't find a way to get the Walker's paper
>   http://dx.doi.org/10.1145/355744.355749
> could you point me to some reference or URL so that I can get
> acquainted with Walker's method?
>

Got it! I found Walker's method in Knuth "The Art of Computer
Programming, Vol 2".

Thank you

-- Marco