Different Methods of Calculating Probability?

magravat

Mr. Simon Bridge,

For calculating probabilities in case of P(y|x) a random discrete probability when x is even, this formula does come close:
Pr(n|i)= 1/ (i*i)(i-2)*(i-1)*(n-i)*((n-i)*sqrt(n-i))*2
The approximation I gave is somewhat correct for even ‘i’ values and the new algorithm is modified:
Pr(n|i)= (i-2)*(n-i)**(i-2)
For 1/Pr(49|6) and other even ‘i’ discrete levels yields a probability of:
7.31250517359741e-08 for Pr(49|6). If n is small, the method is an approximation of probability and is simpler to understand and calculate.


magravat

Simon Bridge

So it is not a method of "computing" probabilities, but for approximating them? Can you also figure out the likely accuracy of the approximation? What is this method's advantage over Stirling's method?

In fact, on my reading this is the sort of information that is missing from your paper - you need to motivate the algorithm (what problem does it solve?) and compare it, directly, with other approximation methods... preferably against a metric justified by the motivation.

If you did supply this information, you need to put it more prominently and in simpler language right at the beginning - and, very briefly, in the abstract.