TY - JOUR ID - 5086 TI - Evaluation of estimation methods for parameters of the probability functions in tree diameter distribution modeling JO - Environmental Resources Research JA - IJERR LA - en SN - 2783-4832 AU - Teimouri, M. AU - Abdolahnezhad, K. AU - Ghalandarayeshi, Sh. AD - Assistant Professor, Gonbad Kavous University, Gonbad Kavous, Iran AD - Assistant Professor, Golestan University, Gorgan, Iran Y1 - 2020 PY - 2020 VL - 8 IS - 1 SP - 25 EP - 40 KW - Least square method KW - Method of maximum product spacings KW - TL-moment KW - Weibull distribution KW - Weighted maximum likelihood estimator DO - 10.22069/ijerr.2020.5086 N2 - One of the most commonly used statistical models for characterizing the variations of tree diameter at breast height is Weibull distribution. The usual approach for estimating parameters of a statistical model is the maximum likelihood estimation (likelihood method). Usually, this works based on iterative algorithms such as Newton-Raphson. However, the efficiency of the likelihood method is not guaranteed since there is no assurance that the Newton-Raphson method for maximizing the log-likelihood function will converge. In such cases, one option is to use a better estimation approach. In this study, several methods were compared for estimating the parameters of two- and three-parameter Weibull distributions. We applied ten methods for two-parameter and twelve methods for three-parameter cases. The data set was collected from natural beech dominated forest in northern Iran. The results demonstrated that among the estimators investigated for two-parameter Weibull distribution, the percentile method outperformed other competitors. In contrast, for three-parameter Weibull distribution, the trimmed L-moment (TL-moment) method and the modified method of moments (type I and type II) outperformed other competitors in terms of Cramer Von-Mises criterion and Kolmogorov-Smirnov criterion, respectively. UR - https://ijerr.gau.ac.ir/article_5086.html L1 - https://ijerr.gau.ac.ir/article_5086_d78c9993e36f451715ebc413e2cf4cf8.pdf ER -