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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 Świętokrzyski 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.
Set of ‘nonparametric’ methods, that don’t make a priori assumption about functional form of empirical distribution was developed as an alternative to the parametric distribution modeling. The kernel estimators are one of such methods, that can be used to describe the frequency of data representing for example DBH records. Kernel smoothing requires the choice of weighting function and bandwidth also called as smoothing parameter or window. The lack of comprehensive analysis on the applicability of particular bandwidth selection methods to model DBH structure gave an impulse to present investigation aimed at determining value and variability of smoothing parameter in black alder stands. The optimal bandwidth was obtained according to six different variants of plug−in method proposed by Altman and Léger. Presented investigations were based on DBH measurements collected in 163 managed black alder stands aged from 6 to 89 years, growing in the west part of the Sandomierz Basin (S Poland). We measured in total 22,530 black alders, from 48 to 359 in individual stand. Stands were characterized by: age, quadratic mean diameter, basal area, mean height, Reineke’s stand density index and standard deviation of DBH. Smoothing parameter was obtained by means of plug−in method with the pilot bandwidth selected by: Silverman’s rule of thumb (nrd0), Scott’s method (nrd), unbiased cross−validation (ucv), biased cross−validation (bcv), method of Sheather and Jones (sj) and one−stage method of Wand and Jones (onestage). The bandwidth was first obtained to real data, then to 100 bootstrap samples of 5, 10, 15 ... and 100 trees from each stand. Smoothing parameters were characterized by mean and variance. Relationship between values of smoothing parameter and stand characteristics was determined. Finally the influence of sample size on value and variability of bandwidth was assessed. Value and variability of smoothing parameter in black alder stands are determined by stand age, sample size and method of bandwidth choice. There is a close relationship between bandwidth and the mean height (r from 0.75 to 0.83), quadratic mean diameter (r from 0.79 to 0.88) and standard deviation of DBH (r from 0.84 to 0.93). Potentially these stand features can be used to predict smoothing parameter values. Minor changes of bandwidth for samples containing above 50 trees together with persistence of standard error give an objective grounds for defining optimal number of diameters, that are necessary to kernel estimation of DBH distribution.
The article presents the results of the analysis of changes of the urban population density in Central Poland in the 20th century using one of the statistical methods meant for the estimation of discrete distributions, the so-called kernel function, and its brief characteristics. The studies cover the period, for which comparable data has been gathered (from 1931 to 2010). The results of the studies have been presented in a textual form and on 9 drawings, showcasing the changes of the population density in Central Poland in the analyzed period.
The objectives of this study are (i) by using selected parametric models and the kernel density estimator to compare the accuracy of approximation of the empirical DBH distributions in stands of different vertical structure as well as the approximation accuracy in the empirical DBH data sets characterised by either average, or small or large differences in the number of DBHs in the neighbouring DBH classes, and (ii) to assess the significance of differences between the selected parametric models and the kernel density estimator. Sampling was carried out in the Świętokrzyski National Park (forest sub-districts: Święta Katarzyna and Święty Krzyż). In the stands of different vertical structure the irregular DBH empirical distributions require reducing the bandwidth of the kernel density estimator. In one-storied, two-storied and selection stands one should employ parametric models, using the kernel density estimator only for the preliminary approximations. However, when approximating the empirical DBH distributions in many-storied stands the kernel density estimation can be much more useful.
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