Open AccessApplication of the discrete distribution in Bayes analYsis of nature area coverage data
Author(s) -
Kęstutis Dučinskas,
Eglė Baltmiškytė,
Martynas Bučas
Publication year - 2012
Publication title -
lietuvos matematikos rinkinys
Language(s) - English
Resource type - Journals
eISSN - 2335-898X
pISSN - 0132-2818
DOI - 10.15388/lmr.b.2012.10
Subject(s) - bayes' theorem , negative binomial distribution , poisson distribution , computer science , count data , binomial distribution , statistical model , statistics , binomial (polynomial) , econometrics , data mining , bayesian probability , mathematics
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.