avgtime - Small D util for your everyday benchmarking needs

[Don Clugston]

On 23/03/12 09:37, Juan Manuel Cabo wrote:
> On Friday, 23 March 2012 at 05:51:40 UTC, Manfred Nowak wrote:
>>
>> | For samples, if it is known that they are drawn from a symmetric
>> | distribution, the sample mean can be used as an estimate of the
>> | population mode.
>
> I'm not printing the population mode, I'm printing the 'sample mode'.
> It has a very clear meaning: most frequent value. To have frequency,
> I group into 'bins' by precision: 12.345 and 12.3111 will both
> go to the 12.3 bin.
>
>>
>> and the program computes the variance as if the values of the sample
>> follow a normal distribution, which is symmetric.
>
> This program doesn't compute the variance. Maybe you are talking
> about another program. This program computes the standard deviation
> of the sample. The sample doesn't need to of any distribution
> to have a standard deviation. It is not a distribution parameter,
> it is a statistic.
>
>> Therefore the mode of the sample is of interest only, when the variance
>> is calculated wrongly.
>
> ???
>
> The 'sample mode', 'median' and 'average' can quickly tell you
> something about the shape of the histogram, without
> looking at it.
> If the three coincide, then maybe you are in normal distribution land.
>
> The only place where I assume normal distribution is for the
> confidence intervals. And it's in the usage help.
>
> If you want to support estimating weird probability
> distributions parameters, forking and pull requests are
> welcome. Rewrites too. Good luck detecting distribution
> shapes!!!! ;-)
>
>
>>
>> -manfred
>
> PS: I should use the t student to make the confidence intervals,
> and for computing that I should use the sample standard
> deviation (/n-1), but that is a completely different story.
> The z normal with n>30 aproximation is quite good.
> (I would have to embed a table for the t student tail factors,
> pull reqs velcome).

No, it's easy. Student t is in std.mathspecial.


>
> PS2: I now fixed the confusion with the confidence interval
> of the variable and the confidence interval of the mu average,
> I simply now show both. (release 0.4).
>
> PS3: Statistics estimate distribution parameters.
>
> --jm
>
>
>