Point and standard error estimation for quantiles of mixed flood distributions

This paper explores the use of finite mixture models in the study of flood frequency distributions with multiple components. It focuses on further methodological developments for finite mixture models, including an accelerated version of the EM algorithm to derive both parameter estimates and the observed information matrix, estimation of the .99 quantile of the mixture distribution, and standard error estimation of the quantile. In case studies, the lognormal finite mixture model will be compared to other models – specifically the widely-used log-Pearson Type III distribution, the Gumbel distribution, and the GEV distribution. A multidimensional gradient plot and information criteria will be discussed as diagnostics for the number of mixing components.