Classical statistical methods do not always provide desired results for every situation. Therefore, new alternative methods of data analysis are in demand. As the computational power becomes more modern, Bayes statistical methods are increasingly applied for statistical data analysis. This article describes several discrete models for analyzing nature area coverage. These models can be applied for analysis of such areas as forests, water ponds, soil, etc. when data is provided in integer data in percent. Poisson and negative binomial distributions are used in this article. Unknown parameters of the models were estimated using Bayes statistical methods in OpenBUGS modeling environment. The models of nature area coverage analysis were implemented using the data of Baltic Sea bottom algae coverage. This article analyzes coverage dependence of abiotic and physical factors.
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