nag_rngs_neg_bin (g05mcc) generates a vector of pseudo-random integers from the discrete negative binomial distribution with parameter m and probability p of success at a trial.

nag_rngs_neg_bin (g05mcc) nag_rngs_neg_bin (g05mcc) generates a vector of pseudorandom integers from the discrete negative binomial distribution with parameter m and probability p of success at a trial.

nag_rand_neg_bin (g05thc) nag_rand_neg_bin (g05thc) generates a vector of pseudorandom integers from the discrete negative binomial distribution with parameter m and probability p of success at a trial.

This paper gives a formula representing all discrete loss distributions of the Panjer class (Poisson, Binomial, and Negative Binomial) in one. Further it provides an overview of the many Negative Binomial variants used by actuaries.

Note: before using this routine, please read the Users ’ Note for your implementation to check the interpretation of bold italicised terms and other implementation-dependent details. 1 Purpose G05THF generates a vector of pseudorandom integers from the discrete negative binomial distribution

Note: before using this routine, please read the Users ’ Note for your implementation to check the interpretation of bold italicised terms and other implementation-dependent details. 1 Purpose G05MCF generates a vector of pseudo-random integers from the discrete negative binomial distribution

Note: before using this routine, please read the Users ’ Note for your implementation to check the interpretation of bold italicised terms and other implementation-dependent details. 1 Purpose G05THF generates a vector of pseudorandom integers from the discrete negative binomial distribution

Note: before using this routine, please read the Users ’ Note for your implementation to check the interpretation of bold italicised terms and other implementation-dependent details. 1 Purpose G05MCF generates a vector of pseudorandom integers from the discrete negative binomial distribution

extensively used for the description of data too heterogeneous to be fitted by a Poisson distribution. Observed samples, however, may be truncated, in the sense that the number

www.amstat.org/publications/jse/v21n1/wroughton.pdf Copyright © 2013 by Jacqueline Wroughton and Tarah Cole all rights reserved. This text may be freely shared among individuals, but it may not be republished in any medium without express written consent from the authors and advance notification of the editor.