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Title: Approximation of the breast height diameter distribution of two-cohort stands by mixture models III Kernel density estimators vs mixture models
Author: Podlaski, Rafal; Roesch, Francis A.;
Source: Sylwan. 158 (6):414-422
Publication Series: Scientific Journal (JRNL)
Description: Two-component mixtures of either the Weibull distribution or the gamma distribution and the kernel density estimator were used for describing the diameter at breast height (dbh) empirical distributions of two-cohort stands. The data consisted of study plots from the Šwietokrzyski National Park (central Poland) and areas close to and including the North Carolina section of the Great Smoky Mountains National Park (USA; southern Appalachians). Kernel density estimators belong to a class of nonparametric density estimators. Nonparametric estimators have no fixed structure and depend upon all the data points to reach an estimate. In this study the Weibull and the gamma mixture distributions were the most versatile models. The results also support the conclusion that there are only minor differences between the parametric models and the kernel density estimates.
Keywords: two-component mixtures, tree diameter distribution, nonparametric goodness-of-fit tests, discrete null distribution.
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Podlaski, Rafal; Roesch, Francis A. 2014. Approximation of the breast height diameter distribution of two-cohort stands by mixture models III Kernel density estimators vs mixture models. Sylwan. 158 (6):414-422. 9 p.
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