A generalized negative binomial (GNB) distribution W M introduced by J m and CONSUL (1971) and was modified by NEL~ON (1976). The probability function of the distribution ie defined by the function p ( z ; m, B, 0) =-P ( 1 -O)m+~z-rforz=O,l, ..., andzerootherwise, where mrO, 0-=8<1 and /3=0 or 1 PP-
A Rapid and Efficient Estimation Procedure for the Negative Binomial Distribution
β Scribed by Dr. A. W. Kemp; Professor C. D. Kemp
- Publisher
- John Wiley and Sons
- Year
- 1987
- Tongue
- English
- Weight
- 453 KB
- Volume
- 29
- Category
- Article
- ISSN
- 0323-3847
No coin nor oath required. For personal study only.
β¦ Synopsis
This paper presents a new noniterative procedure for estimating the parameters of a negative binomial distribution. The procedure uses the first moment equation and an equation based on the weighted sample mean, with weights wzotaz. The selection of a value for a is examined.
A simulation study has been carried out and also the method has been applied to the 35 data sets analysed by MARTIN and KATTI (1965, Biometrics) in order to compare i t with the method of moments and with the method of maximum likelihood (ML). We conclude that the new procedure has greater relative efficiency than the method of moments; i t gives estimates which are consistently close to ML and are easy to calculate.
π SIMILAR VOLUMES
A generalized family of thenegative binomialdistribution is introduced in a paper by SRIVMTAVA, YOOSEY and AEMICD (1986). It is a solution of the difference equation and is called the hyper-negative binomial distribution. Certain properties including the momenta of the distribution are presented. Mo
In many observed processes, data is fit well by a common distribution except for an excess of numbers of the zero class. This may be due to a threshold phenomenon in which no response occurs until a concomitant variable reaches a certain level, and the response is governed by the common probability