A comparative study of different parameter estimation methods for statistical distribution functions in civil engineering applications

In designing civil engineering structures use is made of probabilistic calculation methods. Stress and load parameters are described by statistical distribution functions. The parameters of these distribution functions can be estimated by various methods. An extensive comparison of these different estimation methods is given in this article. Main point of interest is the behaviour of each method for predicting p-quantiles, where p much less than 1. We analyze the performance of the parameter estimation method with respect to its small sample behaviour. Monte Carlo simulations are used in this comparative study added with mathematical proofs. The popularity of the least squares method among engineers is analysed.