The Reciprocal of the Decapitated Negative Binomial Variable

Govindarajulu, Z.

doi:10.2307/2281818

Cited by 4 publications

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“…The model (1) is a limiting form of zero-truncated negative binomial distribution. Negative moments of discrete distributions, mainly the binomial, Poisson and negative binomial have been investigated by various authors [Stephan [1], Grab and Savage [2], Mendenhall and Lehman [3], Govindarajulu [4,5], Tiku [6], Stancu [7], Chao and Strawderman [8], Gupta [9,10], Cressie et al [11], Cressie and Borkent [12] and Roohi [13]. Inverse ascending factorial moments have only been dealt with by Lepage [14] and Jones [15].…”

Section: Introductionmentioning

confidence: 99%

On Size-Biased Logarithmic Series Distribution and Its Applications

Mir¹

2009

TOSPJ

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In this paper, a size-biased logarithmic series distribution (SBLSD), a particular case of the weighted logarithmic series distribution, taking the weights as the variate values is defined. The moments and recurrence relation of (SBLSD) are obtained. Negative moments and inverse ascending factorial moments of the size-biased logarithmic series distribution have been derived in terms of hyper-geometric function. Recurrence relations for these moments have also been derived using properties of hyper-geometric functions. Different estimation methods for the parameter of the model are discussed. R-Software has been used for making a comparison among the three different estimation methods and with the logarithmic series distribution.

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Section: Introductionmentioning

confidence: 99%

On Size-Biased Logarithmic Series Distribution and Its Applications

Mir¹

2009

TOSPJ

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“…Introduction. Inverse moments of the binomial, Poisson, negative binomial and the hypergeometric distributions truncated at zero have been studied in [31, [4], [51, [6], [8], [10], [11] and [12]. Also, inverse moments of the gamma and the beta distributions have been used as approximations to the inverse moments of the positive discrete random variables.…”

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confidence: 99%

Theory of Inverse Moments

Govindarajulu¹

1962

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The characteristic function for inverse moments called the inverse characteristic function (inverse c.f.) is defined. Liafounov's inequality for inverse moments is obtained. Various properties, in particular, the uniqueness property (also called the inversion formula), limit and continuity properties, are studied. Illustrations are provided wherever necessary. Many results admit multivariate generalizations. Inverse order statistics are defined. Also, some applications of inverse moments are considered.

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On negative moments of generalized poisson distribution

Gupta

1979

Series Statistics

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The Reciprocal of the Decapitated Negative Binomial Variable

Cited by 4 publications

References 0 publications

On Size-Biased Logarithmic Series Distribution and Its Applications

On Size-Biased Logarithmic Series Distribution and Its Applications

Theory of Inverse Moments

On negative moments of generalized poisson distribution

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