On negatively skewed extended generalized logistic distribution
A. K. Olapade (2005)
Kragujevac Journal of Mathematics
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A. K. Olapade (2005)
Kragujevac Journal of Mathematics
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Zofia Grudzień, Dominik Szynal (1995)
Applicationes Mathematicae
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We give characterizations of the uniform distribution in terms of moments of order statistics when the sample size is random. Special cases of a random sample size (logarithmic series, geometrical, binomial, negative binomial, and Poisson distribution) are also considered.
Ahsanullah, M. (2009)
Bulletin of the Malaysian Mathematical Sciences Society. Second Series
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M.O. Ojo, A.K. Olapade (2003)
Kragujevac Journal of Mathematics
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Ilona Kopocińska (1999)
Applicationes Mathematicae
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The bivariate negative binomial distribution is introduced using the Marshall-Olkin type bivariate geometrical distribution. It is used to the estimation of the distribution of the number of accidents in standard data.
Matthev O. Ojo, A.K. Olapade (2004)
Kragujevac Journal of Mathematics
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Shola Adeyemi (2004)
Kragujevac Journal of Mathematics
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Bolesław Kopociński (1999)
Applicationes Mathematicae
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We define a multivariate negative binomial distribution (MVNB) as a bivariate Poisson distribution function mixed with a multivariate exponential (MVE) distribution. We focus on the class of MVNB distributions generated by Marshall-Olkin MVE distributions. For simplicity of notation we analyze in detail the class of bivariate (BVNB) distributions. In applications the standard data from [2] and [7] and data concerning parasites of birds from [4] are used.
Roşca, Alin V., Roşca, Natalia C. (2010)
Acta Universitatis Apulensis. Mathematics - Informatics
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Shola Adeyemi, Mathew Oladejo Ojo (2003)
Kragujevac Journal of Mathematics
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Alicja Jokiel-Rokita (1998)
Applicationes Mathematicae
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A problem of minimax prediction for the multinomial and multivariate hypergeometric distribution is considered. A class of minimax predictors is determined for estimating linear combinations of the unknown parameter and the random variable having the multinomial or the multivariate hypergeometric distribution.