Abstract:
The method of moving separation of mixtures is applied to the problem of statistical modeling of regularities in explicit and latent turbulent heat fluxes. The six-hour observations in the Atlantic region (NCEP-NCAR, 1948–2008) are used as initial data. The basic approximate mathematical model is a finite normal mixture with parameters depending on time. The methodology of moving separation of mixtures allows one to analyze the regularities in the variation of parameters and to capture the variability which can be associated with the trend as well as the irregular variation. An approach is proposed to the determination of the proportion of extreme observations in the original sample.
Keywords:finite normal mixtures; moving separation of mixtures; probabilistic models; data mining.