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IJSTR >> Volume 8 - Issue 9, September 2019 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Negative Binomial - Geeta Distributionand Some Of Its Property

[Full Text]

 

AUTHOR(S)

Sakthivel K M, Rajkumar J

 

KEYWORDS

Negative Binomial Distribution, Geeta Distribution, Second Lagrange Expansion, Recurrence Relations, Convolution Property and Maximum Likelihood Estimation.

 

ABSTRACT

In this paper, we derived a probability mass function of new discrete probability distribution named as negative binomial - Geeta distribution and it is obtained by usingLagrange expansion of second kind. We studied some important characteristics of this distribution such as convolution property, probability generating function, etc. Further, it is shown that the proposed distribution is in the form of modified power series distribution(MPSD). Maximum likelihood method is used to estimate the parameters of the distribution.

 

REFERENCES

[1]. Arbous,A.G.and Sichel,H. S. (1954).“New techniques for the analysis of absenteeism data”,Biometrika,41, 77-90.
[2]. Consul, P.C. and Shenton,L.R.(1972).“Use of Lagrange expansion for generation generalized probability distribution”, SIAM Journal of Applied Mathematics, 23,239-248.
[3]. Consul, P.C. and Shenton,L.R.(1973).“Some interesting properties of Lagrangian distribution”,Communication in Statistics, 2, 263-272.
[4]. Consul, P.C. (1990a).“Geeta distribution and its properties”, Communication in Statistics-Theory and Methods, 19, 3051-3068.
[5]. Consul, P.C.(1990b).“Two stochastic model for the Geeta distribution”,Communication in Statistics-Theory and Methods,19,3699-3706.
[6]. Consul, P.C.(1990c).“New class of location-parameter discrete probability distribution and their characterizations”,Communications in Statistics – Theory and Methods,19, 4653-4666.
[7]. Consul, P.C. and Famoye,F. (2001).“On Lagrangian distribution of the second kind”,Communications in Statistics-Theory and Methods, 30,165-178.
[8]. Consul, P.C. and Famoye,F. (2005).“Devprobability distribution and some of its applications”,Advances and Applications in Statistics, 5(3), 17-30.
[9]. Consul, P.C. and Famoye,F. (2006).“Harish probability distribution and its applications”,Journal of Statistical theory and Applications, 5(1), 17-30.
[10]. Gupta, R.C. (1974).“Modified power series distribution and some of its applications”, Sankhya series B,35, 288-298.
[11]. Gupta, R.C. (1975).“Maximum likelihood estimation of a modified power series distribution and some of its applications”,Communications in Statistics, 2, 687-697.
[12]. Janardan, K.G. (1997).“A wider class of Lagrange distributions of the second kind”,Communications in Statistics – Theory and Methods,26,2087-2091.
[13]. Janardan, K.G. and Rao,B.R. (1983).“Lagrange distribution of the second kind and weighted distribution”, SIAM Journal of Applied Mathematics, 43,302-313.
[14]. Janardan, K.G. (1987).“Weighted Lagrangian Distributions and their characterizations”, SIAM Journal of Applied Mathematics, 47,2,411-415.
[15]. Johnson, N.L. Kotz, S. and Kemp,A.W. (1992).“Univariate Discrete Distributions”, 2nd edition. John Wiley & sons, Inc., New York, NY
[16]. Kumar, A.(1981).“Some application of Lagrangian distribution in queueing theory and epidemiology”,Communication in Statistics-Theory and Methods, 10,1429-1436.
[17]. Li, S. Famoye, F. and Lee, C. (2006).“On some extension of the Lagrangian probability distributions”,Far East journal of Theoretical and Statistics,6,91-100
[18]. Li, S. Famoye, F.and Lee, C. (2008).“On certain mixture distributions based on Lagrangian probability models”,Journal of probability statistical science,6,91-100
[19]. Lindskog, F.and McNeil, A.J. (2003).“Common Poisson shock models: applications insurance and credit risk modelling”,ASTIN Bull 33, 209-238.
[20]. Shubiao Li, Dennis Black, Carl Lee, Felix Famoye and Sung Li. (2010).“Dependence Models Arising from the Lagrangian Probability Distributions”, Communication in Statistics-Theory and Methods, 39,1729-1742.