Empirical comparisons of goodness-of-fit tests for binomial distributions based on fuzzy representations

Abstract

Fuzzy representations of a real-valued random variable have been introduced with the aim of capturing relevant information on the distribution of the variable, through the corresponding fuzzy-valued mean value. In particular, characterizing fuzzy representations of a random variable allow us to capture the whole information on its distribution. One of the implications from this fact is that tests about fuzzy means of fuzzy random variables can be applied to develop goodness-of-fit tests. In this paper we present empirical comparisons of goodness-of-fit tests based on some convenient fuzzy representations with well-known procedures in case the null hypothesis relates to some specified Binomial distributions. © 2008 Springer-Verlag Berlin Heidelberg.