Abstract
This paper proposes the log shifted gamma (LSG) approximation to model the sum of M lognormal distributed random variables. The closed-form probability density function (PDF) of the resulting LSG random variable (RV) is presented and its parameters are derived from those of the M individual lognormal RV by using an iterative moment matching technique. Simulation results on the cumulative distribution function (CDF) of sum of M lognormal random variables in different conditions are used as reference curves to compare various approximation techniques. LSG approximation is found to provide better accuracy over a wide CDF range, especially for large M and/or standard deviation.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
