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From: Milan Rusev (milan.rusev_at_[hidden])
Date: 2008-03-25 04:16:48

OK, a statistics library sounds better to me, too.

So how about that (speaking in pseudo code):

There is a base class:



get_probability(value); // P(value)

get_comulutative_probability(value); //P(x <= value)






Specific distributions will derive from it and expose their parameters too;

discrete distributions may have a method get_values().


distribution create_distribution(samples, distribution_type); // given a
specific distribution and

a set of samples find the MLE (the parameters of the distribution);
implemented specifically for each distribution

distribution create_ distribution(samples); // given a set of samples
approximate an

unknown distribution (e.g. with a Monte Carlo or smth like this);

maybe the method for the generation will be a parameter too.

There may be methods of inferring some properties of a distribution without
generating the whole of it first.


distribution create_joint_distr(distribution, distribution);

distribution create_sum(distribution, distribution);

distribution create_difference(distribution, distribution);

Other things I can think of.

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