Estimation of Logistic Parameters Using a Fuzzy Least-squares Method and Different Types of Moments

The main attention of this paper is to deduce the estimators of the parameters of the Logistic distribution using five estimating methods, namely, the fuzzy least-squares method, the LQ-moments (linear quantile moments) with three cases (trimean, median and Gastwirth), TL-moments (trimmed linear moments) with different individual cases, L-moments (linear moments) and the maximum likelihood method. Also, a comparison between the performances of these estimators using simulations is given. According to these comparisons, it is shown that the proposed fuzzy least-squares algorithm is preferred for large sample size.