On the linear combination of independent logistic random variables
Abstract
In this work the exact distribution of the linear combination of p independent logistic random variables is studied. It is shown that the exact distribution may be represented as a shifted infinite sum of independent random variables distributed as the difference of two independent Generalized Integer Gamma distributions. In addition, two near-exact approximations are developed for this distribution. Numerical studies are conducted to access the degree of precision and also the computational performance of these approximations. The developed methodology is used to derive near-exact approximations for the linear combination of independent generalized logistic random variables.References
N. Balakrishnan, Handbook of the logistic distribution, Marcel Dekker, New York, 1992.
J. Berkson, Application of the logistic function to bioassay. Journal of American Statistical Association, 39, 357-365, 1944.
C. I. Bliss, Statistics in biology, vol. 1, McGraw-Hill, New York, 1970.
C. A. Coelho, The Generalized Integer Gamma Distribution—A Basis for Distributions in Multivariate Statistics. Journal of Multivariate Analysis, 64, 86-102, 1998.
C. A. Coelho, The Generalized Near-Integer Gamma Distribution: A Basis for ‘Near-Exact’ Approximations to the Distribution of Statistics which are the Product of an Odd Number of Independent Beta Random Variables. Journal of Multivariate Analysis, 89, 191-218, 2004.
C. A. Coelho, J. T. Mexia, Product and Ratio of Generalized Gamma Ratio Random Variables: Exact and Near-exact Distributions Applications. LAP LAMBERT Academic Publishing, 2010.
D. R. Cox, The regression analysis of binary sequences (with discussion), Journal of Royal Statistical Society B, 20, 215-242, 1958.
J. H. Davies, The Physics of Low-dimensional Semiconductors: An Introduction, Cambridge University Press, 1998.
E. O. George, G. S. Mudholkar, On the convolution of logistic random variables, Metrika, 30, 1-13, 1983.
N. L. Johnson, S. Kotz, N. Balakrishnan, Continuous Univariate Distributions, vol. 2, second ed., Wiley, New York, 1995.
Y. L. Luke, The Special Functions and their Approximations, vol. 1, Academic Press, 1969.
F. J. Marques, C. A. Coelho and B. C. Arnold, A general near-exact distribution theory for the most common likelihood ratio test statistics used in Multivariate Analysis. Test, 20, 180-203, 2011.
F. J. Marques, C. A. Coelho, M. de Carvalho, On the distribution of linear combinations of independent Gumbel random variables. Statistics and Computing, 25, 683-701, 2015.
F. Oberhettinger, Z. W. Birnbaum, E. Lukacs, Fourier Transforms of Distributions and Their Inverses: A Collection of Tables. Probability and mathematical statistics, Elsevier Science, 2014.
M. O. Ojo, Approximations of the sum of random variables from generalized logistic distribution. Kragujevac J. Math., 24, 135-145, 2002.
F. R. Oliver, Notes on the logistic curve for human population. Journal of the Royal Statistical Society Series A, 145, 359-363, 1982.
G. Olusegun, M. O. Ojo, On a Generalization of the Logistic distribution. Ann. Inst. Statist. Math., 32, 161-169, 1980.
L. C. de S. M. Ozelim, C. E. G. Otiniano, P. N. Rathie, On the linear combination of n logistic random variables and reliability analysis. South East Asian J. of Math. & Math. Sci., 12, 19-34, 2016.
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