AUTHOR AND 
SRESHTA DHIMAN Email of Corresponding Author: – sdhimanjee@gmail.com 
KEYWORDS: 
HFunction, Laplace transform, random variables 
Issue Date: 
November, 2016 
Pages: 
299303 
ISSN: 
23198044 (Online) – 2231346X (Print) 
Source: 
Vol.28 – No.6 
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DOI: 
http://dx.doi.org/10.22147/juspsA/280602 
ABSTRACT:
The aim of this section is to obtain the distribution of mixed sum of two independent random variables with different probability density functions. One with probability density function defined in finite range and the other with probability density function defined in infinite range and associated with product of general class of polynomials and generalized H–function of two variables. The method used is based on Laplace transform and it’s inverse. The result obtained here is quite general in nature and is capable of yielding a large number of corresponding new and known results merely by specializing the parameters involved therein. To illustrate, some special cases of our main result are also given
Copy the following to cite this Article:
SRESHTA DHIMAN, “The Distribution of the Sum of Mixed Independent Random Variables Involving Generalized HFunctions of two Variables”, Journal of Ultra Scientist of Physical Sciences, Volume 28, Issue 6, Page Number 299303, 2016
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SRESHTA DHIMAN, “The Distribution of the Sum of Mixed Independent Random Variables Involving Generalized HFunctions of two Variables”, Journal of Ultra Scientist of Physical Sciences, Volume 28, Issue 6, Page Number 299303, 2016
The aim of this section is to obtain the distribution of mixed sum of two independent random variables with different probability density functions. One with probability density function defined in finite range and the other with probability density function defined in infinite range and associated with product of general class of polynomials and generalized H–function of two variables. The method used is based on Laplace transform and it’s inverse. The result obtained here is quite general in nature and is capable of yielding a large number of corresponding new and known results merely by specializing the parameters involved therein. To illustrate, some special cases of our main result are also given