Mark R. Diggory wrote:
<cut/>
>
>
> I think maybe this should be returning the more generic
> StatisticalSummary interface. If you are returning precalculated
> results, you do not exactly want to expose the underlying implementation
> to modification by the user.
>
> StatisticalSummary[] sampleStats ...
That's good idea
> If your going to be preserving the original/bootstrap values in a
> double[][], then the Standard "DescriptiveStatisticsImpl" could be used.
>
> public interface FullStatisticalSummary {
> public abstract double getMean();
> public abstract double getVariance();
> public abstract double getStandardDeviation();
> public abstract double getMax();
> public abstract double getMin();
> public abstract long getN();
> public abstract double getSum();
> public abstract double getPercentile(double p);
> ...
> }
>
> or more simply,
>
> public interface FullStatisticalSummary extends StatisticalSummary{
> public abstract double getPercentile(double p);
> ...
> }
Exactely, but the point is that we have to preserve original/bootstrap
values and EmpiricalDistribution is not storing them - internally it keeps
data
in the array of bins. As I understand this was the aim - we don't have to
keep the whole data set in order to get important information about the
empirical distribution. If a data set is huge this is a true gain.
If, on the other hand, I want to keep the whole data set then I can easily
use
other tools to calculate any statistics I want so I don't need to use
EmpiricalDistribution.
Documentation for EmpiricalDistribution gives two example applications
of this interface - preparing data for drawing a histogram and provide
methods to draw random numbers from such a distribution. I am
wondering if making EmpiricalDistribution responsible for other tasks
like handling bootstrap samples or even doing bootstrap would not
make it to complicated to use.
Piotr
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