(a,b,0) Class Of Distributions
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In probability theory, a member of the (''a'', ''b'', 0) class of distributions is any distribution of a discrete random variable ''N'' whose values are nonnegative integers whose probability mass function satisfies the recurrence formula : \frac = a + \frac, \qquad k = 1, 2, 3, \dots for some real numbers ''a'' and ''b'', where p_k = P(N = k). Only the Poisson,
binomial Binomial may refer to: In mathematics *Binomial (polynomial), a polynomial with two terms * Binomial coefficient, numbers appearing in the expansions of powers of binomials *Binomial QMF, a perfect-reconstruction orthogonal wavelet decomposition ...
and negative binomial distributions satisfy the full form of this relationship. These are also the three discrete distributions among the six members of the natural exponential family with quadratic variance functions (NEF–QVF). More general distributions can be defined by fixing some initial values of ''pj'' and applying the recursion to define subsequent values. This can be of use in fitting distributions to empirical data. However, some further well-known distributions are available if the recursion above need only hold for a restricted range of values of ''k'': for example the logarithmic distribution and the discrete
uniform distribution Uniform distribution may refer to: * Continuous uniform distribution * Discrete uniform distribution * Uniform distribution (ecology) * Equidistributed sequence In mathematics, a sequence (''s''1, ''s''2, ''s''3, ...) of real numbers is said to be ...
. The (''a'', ''b'', 0) class of distributions has important applications in actuarial science in the context of loss models.


Properties

Sundt proved that only the
binomial distribution In probability theory and statistics, the binomial distribution with parameters ''n'' and ''p'' is the discrete probability distribution of the number of successes in a sequence of ''n'' independent experiments, each asking a yes–no quest ...
, the Poisson distribution and the
negative binomial distribution In probability theory and statistics, the negative binomial distribution is a discrete probability distribution that models the number of failures in a sequence of independent and identically distributed Bernoulli trials before a specified (non-r ...
belong to this class of distributions, with each distribution being represented by a different sign of ''a''. Furthermore, it was shown by Fackler that there is a universal formula for all three distributions, called the (united) Panjer distribution. The more usual parameters of these distributions are determined by both ''a'' and ''b''. The properties of these distributions in relation to the present class of distributions are summarised in the following table. Note that W_N(x)\, denotes the probability generating function. Note that the Panjer distribution reduces to the Poisson distribution in the limit case \alpha \rightarrow \pm\infty; it coincides with the negative binomial distribution for positive, finite real numbers \alpha\in \mathbb_, and it equals the binomial distribution for negative integers -\alpha \in \mathbb.


Plotting

An easy way to quickly determine whether a given sample was taken from a distribution from the (''a'',''b'',0) class is by graphing the ratio of two consecutive observed data (multiplied by a constant) against the ''x''-axis. By multiplying both sides of the recursive formula by k, you get : k \, \frac = ak + b, which shows that the left side is obviously a linear function of k. When using a sample of n data, an approximation of the p_k's need to be done. If n_k represents the number of observations having the value k, then \hat_k = \frac is an unbiased estimator of the true p_k. Therefore, if a linear trend is seen, then it can be assumed that the data is taken from an (''a'',''b'',0) distribution. Moreover, the slope of the function would be the parameter a, while the ordinate at the origin would be b.


See also

*
Panjer recursion The Panjer recursion is an algorithm to compute the probability distribution approximation of a compound random variable S = \sum_^N X_i\, where both N\, and X_i\, are random variables and of special types. In more general cases the distribution of ...


References

{{ProbDistributions, families Discrete distributions Systems of probability distributions Actuarial science