In probability and statistics the extended negative binomial distribution is a discrete probability distribution extending the negative binomial distribution. It is a truncated version of the negative binomial distribution for which estimation methods have been studied.

In the context of actuarial science, the distribution appeared in its general form in a paper by K. Hess, A. Liewald and K.D. Schmidt when they characterized all distributions for which the extended Panjer recursion works. For the case m = 1, the distribution was already discussed by Willmot and put into a parametrized family with the logarithmic distribution and the negative binomial distribution by H.U. Gerber.

Probability mass function

For a natural number m ≥ 1 and real parameters p, r with 0 < p ≤ 1 and –m < r < –m 1, the probability mass function of the ExtNegBin(m, r, p) distribution is given by

f ( k ; m , r , p ) = 0  for  k { 0 , 1 , , m 1 } {\displaystyle f(k;m,r,p)=0\qquad {\text{ for }}k\in \{0,1,\ldots ,m-1\}}

and

f ( k ; m , r , p ) = ( k r 1 k ) p k ( 1 p ) r j = 0 m 1 ( j r 1 j ) p j for  k N  with  k m , {\displaystyle f(k;m,r,p)={\frac {{k r-1 \choose k}p^{k}}{(1-p)^{-r}-\sum _{j=0}^{m-1}{j r-1 \choose j}p^{j}}}\quad {\text{for }}k\in {\mathbb {N} }{\text{ with }}k\geq m,}

where

( k r 1 k ) = Γ ( k r ) k ! Γ ( r ) = ( 1 ) k ( r k ) ( 1 ) {\displaystyle {k r-1 \choose k}={\frac {\Gamma (k r)}{k!\,\Gamma (r)}}=(-1)^{k}\,{-r \choose k}\qquad \qquad (1)}

is the (generalized) binomial coefficient and Γ denotes the gamma function.

Probability generating function

Using that f ( . ; m, r, ps) for s ∈ (0, 1] is also a probability mass function, it follows that the probability generating function is given by

φ ( s ) = k = m f ( k ; m , r , p ) s k = ( 1 p s ) r j = 0 m 1 ( j r 1 j ) ( p s ) j ( 1 p ) r j = 0 m 1 ( j r 1 j ) p j for  | s | 1 p . {\displaystyle {\begin{aligned}\varphi (s)&=\sum _{k=m}^{\infty }f(k;m,r,p)s^{k}\\&={\frac {(1-ps)^{-r}-\sum _{j=0}^{m-1}{\binom {j r-1}{j}}(ps)^{j}}{(1-p)^{-r}-\sum _{j=0}^{m-1}{\binom {j r-1}{j}}p^{j}}}\qquad {\text{for }}|s|\leq {\frac {1}{p}}.\end{aligned}}}

For the important case m = 1, hence r ∈ (–1, 0), this simplifies to

φ ( s ) = 1 ( 1 p s ) r 1 ( 1 p ) r for  | s | 1 p . {\displaystyle \varphi (s)={\frac {1-(1-ps)^{-r}}{1-(1-p)^{-r}}}\qquad {\text{for }}|s|\leq {\frac {1}{p}}.}

References


Negatives BinomialExperiment / Verteilung Definition, Beispiele ISNCA

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Negative Binomial Distribution PDF

TemplateNegative binomial distribution Wikipedia, the free encyclopedia

PPT The Negative Binomial Distribution PowerPoint Presentation, free