![]() ![]() Because dg lies very close to this point, it correlates empirically very tightly with this parameter and thus allows for a trustful simple estimation. One of these is the main (scale) parameter β being given at a remarkable point of the function free, i.e. The Weibull distribution offers the advantage of simple but reliable estimation procedures. Their performances are assessed in comparison to real distributions from a wide database of permanent Swiss yield plots repeatedly measured (time series) for Norway spruce ( Picea abies (L.) Karst.) and European beech ( Fagus sylvatica L.). They use a remarkable, empiric property of the Weibull function. The aim of this paper is to compare different methods of estimating the Weibull distribution parameters, partly based on parameter recovery method (PRM). This can be applied for yield model construction or inventory purposes. One of the most appealing applications of diameter distribution functions is to predict compliant stand diameters without needing to tally all stems, but in determining the function parameters only on the base of simple stand characteristics. This feature could be used for growth modelling as well as inventory purposes, at least for monospecific and even-aged stands and, maybe more, because this feature is proper to the function itself. This is related principally with a particular feature of the Weibull distribution function, and the empirical dependency of the main scale parameter α + β from the mean quadratic diameter (dg): This allows the prediction of the parameter β with an unexpectedly high likelihood. Using the three characteristic points of a forest stand, dg (mean quadratic diameter), d min (diameter of the smallest tree) and d max (diameter of the largest tree), appears informative enough to determine the parameters of the whole diameter distribution and, hence, the standing volume, with an accuracy of 2–3%. ![]()
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