On 14/01/2019 20:11, duncan smith wrote:
> Hello,
> Just checking to see if anyone has attacked this problem before
> for cases where the population size is unfeasibly large. i.e. The number
> of categories is manageable, but the sum of the frequencies, N,
> precludes simple solutions such as
On 15/01/2019 17:59, Ian Hobson wrote:
> Hi,
>
> If I understand your problem you can do it in two passes through the
> population.
>
The thing is that I start with the population histogram and I want to
generate a sample histogram. The population itself is too large to deal
with each population
Hi,
If I understand your problem you can do it in two passes through the
population.
First, however, lets work through taking a sample of 2 from 7 to
demonstrate the method.
Take the first element with a probability of 2/7. (Note 1).
If you took it, you only want 1 more, so the probability
On 15/01/2019 02:41, Spencer Graves wrote:
>
>
> On 2019-01-14 18:40, duncan smith wrote:
>> On 14/01/2019 22:59, Gregory Ewing wrote:
>>> duncan smith wrote:
Hello,
Just checking to see if anyone has attacked this problem before
for cases where the population size is unfeas
On 2019-01-14 18:40, duncan smith wrote:
On 14/01/2019 22:59, Gregory Ewing wrote:
duncan smith wrote:
Hello,
Just checking to see if anyone has attacked this problem before
for cases where the population size is unfeasibly large.
The fastest way I know of is to create a list of cumul
On 14/01/2019 22:59, Gregory Ewing wrote:
> duncan smith wrote:
>> Hello,
>> Just checking to see if anyone has attacked this problem before
>> for cases where the population size is unfeasibly large.
>
> The fastest way I know of is to create a list of cumulative
> frequencies, then generat
duncan smith wrote:
Hello,
Just checking to see if anyone has attacked this problem before
for cases where the population size is unfeasibly large.
The fastest way I know of is to create a list of cumulative
frequencies, then generate uniformly distributed numbers and
use a binary search
