Simulation of random fuzzy variables: an empirical approach to statistical/probabilistic studies with fuzzy experimental data

In this paper, we simulate different types of random fuzzy variables to get some conclusions concerning fuzzy-valued random variables. This simulation has been carried out to illustrate certain limit results formalizing the convergence of the arithmetic mean of sample fuzzy data to the population mean (or expected value of the random fuzzy variable), like the well-known strong law of large numbers (SLLN) and the law of iterated logarithm (LIL). Since the theoretical results have recently been proved, this simulation analysis means a complementary study in which we can determine sample sizes providing us with suitable approximations. Future directions regarding statistical inference with fuzzy data and other applications are finally commented on.