Summary
Another bivariate generalisation (Type V) of the non-central negative binomial distribution is considered. This generalisation is constructed (i) as a latent structure model; (ii) as an extension of an accident proneness model investigated by Edwards/Gurland (1961); and (iii) as a reversible stochastic counter model. The third construction gives, as a result, an apparently new formulation of the Edwards/Gurland model. The probabilities, moments, recurrence formulas and some properties are given. An application to the data used by Holgate (1966) is considered.
Similar content being viewed by others
References
Chihara TS (1978) An introduction to orthogonal polynomials. New York
Consael R (1952) Sur les processus composés de Poisson á deux variables aléatoires. Académie Royale de Belgique, Classe des Sciences, Mémoires 27:4–43
Edwars CB, Gurland J (1961) A class of distributions applicable to accidents. J Amer Statist Ass. 56:503–517
Erdélyi A (1953) Higher transcendental functions, vol II. McGraw Hill
Goodman LA (1974) Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika 61:215–231
Holgate P (1964) Estimation for the bivariate Poisson distribution. Biometrika 51:241–245
Holgate P (1966) Bivariate generalizations of Neyman's typeA distribution. Biometrika 53:241–245
Johnson NL (1957) Uniqueness of a result in the theory of accident proneness. Biometrika 44:530–531
Kemp AW (1968) A wide class of discrete distributions and the associated differential equations. Sankhya A 30:401–410
Kemp CD, Kemp AW (1965) Some properties of the Hermite distribution. Biometrika 52:381–394
Laha RG (1954) On some properties of the Bessel function distributions. Bull Calcutta Math Soc 46:59–72
Lai CD (1978) A note on central limit theorem for the Wold's Markov process of gamma intervals. Tamkang J Math 9 (2):209–215
Lai CD (1981) On conditional correlation coefficients of a Wold Markov process of gamma intervals. Aust J Statist 23 (2):232–237
Lampard DG (1965) A stochastic process whose successive intervals between events form a first order Markov chain — I. Report No. MEE 65-1. Electrical Engineering Dept., Monash University, Australia
Lampard DG (1968) A stochastic process whose successive intervals between events form a first order Markov chain — I. J Appl Prob 5:648–668
Lee PA (1968) A study of some stochastic processes in Communication Engineering. PhD Thesis Monash Unviersity, Australia
Lee PA, Ong SH (1981) The bivariate non-central negative binomial distributions. Research Report 12/81, Dept. of Mathematics, University of Malaya, Malaysia (to appear in Metrika)
Mitchell CR, Paulson AS (1981) A new bivariate negative binomial distribution. Navals Res Logistics Quart 28:359–374
Ong SH, Lee PA (1979) The non-central negative binomial distribution. Biom J 21:611–627
Ong SH, Lee PA (1982) On the bivariate negative binomial distribution of Mitchell and Paulson. Research Report 5/82, Dept. of Mathematics, University of Malaya, Malaysia, (to appear in Navals Res Logistics Quart 1985)
Phatarfod RM (1971) Some approximate results in renewal and dam theory. J Aust Math Soc 12:425–432
Plunkett IG, Jain GC (1975) Three generalised negative binomial distributions. Biom J 17: 286–302
Sneddon IN (1961) Special functions of mathematical physics and chemistry. Edinburgh
Subrahmaniam Ko (1966) A test for “intrinsic correlation” in the theory of accident proneness. J R Statist Soc B 28:180–189
Subrahmaniam Ko, Subrahmaniam Ka (1973) On the estimation of the parameters in the bivariate negative binomial distribution. J R Statist Soc B 35:131–146
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Ong, S.H., Lee, P.A. Bivariate non-central negative binomial distribution: Another generalisation. Metrika 33, 29–46 (1986). https://doi.org/10.1007/BF01894724
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/BF01894724