THE FITTING OF BINOMIAL DISTRIBUTIONS

A continuous approximation fitting to the discrete distributions using ODE

The probability density functions fitting to the discrete probability functions has always been needed, and very important. This paper is fitting the continuous curves which are probability density functions to the binomial probability functions, negative binomial geometrics, poisson and hypergeometric. The main key in these fittings is the use of the derivative concept and common differential ...

determinant of the hankel matrix with binomial entries

abstract in this thesis at first we comput the determinant of hankel matrix with enteries a_k (x)=?_(m=0)^k??((2k+2-m)¦(k-m)) x^m ? by using a new operator, ? and by writing and solving differential equation of order two at points x=2 and x=-2 . also we show that this determinant under k-binomial transformation is invariant.

Testing Poisson Binomial Distributions

A Poisson Binomial distribution over n variables is the distribution of the sum of n independent Bernoullis. We provide a sample near-optimal algorithm for testing whether a distribution P supported on {0, . . . , n} to which we have sample access is a Poisson Binomial distribution, or far from all Poisson Binomial distributions. The sample complexity of our algorithm is O(n) to which we provid...

Binomial and multinomial distributions

Discrete Distributions Connected with the Bivariate Binomial

A new class of multivariate discrete distributions with binomial and multinomial marginals is studied. This class of distributions is obtained in a natural manner using probabilistic properties of the sampling model considered. Some possible applications in game theory, life testing and exceedance models for order statistics are discussed.