A comparison of estimation methods for fitting Weibull and Johnson’s SB functions to pedunculate oak (Quercus robur) and birch (Betula pubescens) stands in northwest Spain

Gorgoso-Varela, José Javier; Alboreca, Alberto Rojo

doi:10.5424/fs/2014233-04939

Cited by 14 publications

(3 citation statements)

References 11 publications

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“…Statistical functions are often used to model diameter distributions of forest stands (e.g., Poudel & Cao, 2013;Gorgoso-Varela & Rojo-Alboreca, 2014;Ogana et al, 2017), and have become an important part of forest management and planning. Diameter distribution forms the link between stand level and tree level models (Nord-Larsen & Cao, 2006).…”

Section: Introductionmentioning

confidence: 99%

“…For example, Poudel & Cao (2013) compared several methodologies to estimate the parameters of Weibull for tree diameter characterisation. Similarly, Gorgoso-Varela & Rojo-Alboreca (2014) evaluated different estimation methods for fitting the Johnson's SB and Weibull functions to pedunculate oak (Quercus robur L.) and birch (Betula sp.) stands in Northwest Spain.…”

Section: Introductionmentioning

confidence: 99%

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A percentile-based estimator for the log-logistic function: Application to forestry

Ogana

2020

Forestry Studies

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Developing a simplified estimation method without compromising the performance of the distribution is germane to forest modelling. Few estimation methods exist for the Log-Logistic distribution and are relatively complex. A simplified estimator for the Log-Logistic parameters will increase its application in diameter distribution yield systems. Therefore, in this study, a percentile-based estimator was applied for the Log-Logistic distribution. The Kolmogorov-Smirnov, Anderson-Darling and Cramer-von Mises statistics were used to evaluate the method in two natural forest stands and two monospecific plantations of Gmelina arborea Roxb. and Tectona grandis Linn. f. in Nigeria. The parameter recovery model (PRM) and parameter prediction model (PPM) were used to predict the diameter distributions of independent stands of G. arborea and T. grandis. The results showed that the percentile estimator did not compromise the quality of fits of the Log-Logistic function across the four forest stands and are comparable to the maximum likelihood estimator. The 25th and 75th, and 40th and 80th were the best sample percentiles for the estimator. The predicted diameter distributions of G. arborea and T. grandis stands from the PRM and PPM were reasonable and compare well with the observed distribution. Thus, either of the models can be incorporated into the growth and yield system of forest stand management.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A percentile-based estimator for the log-logistic function: Application to forestry

Ogana

2020

Forestry Studies

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“…The diameter distributions of these stands have been described using the Weibull function fitted with maximum likelihood and percentiles estimators (e.g., Ajayi 2013, Ekpa et al 2014, Saka 2014, Ogana and Ekpa 2020. Other studies that have applied the moments, least squares, percentiles, maximum likelihood methods for the Weibull function outside Nigeria include Poudel and Cao (2013), Gorgoso-Varela and Rojo-Alboreca (2014), Sun et al (2019), etc. Inappropriate choice of estimator to derive the diameter distribution could affect the quality of fit and overall management decision.…”

Section: Introductionmentioning

confidence: 99%

An evaluation of ten estimators for fitting two-parameter weibull function to Nigerian forest stands

Ogana

2020

Eurasian Journal of Forest Science

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The quality fit produce by distribution function such as the Weibull depends to an extent the type of estimator used to derive its parameters. Inappropriate choice of estimator could affect management decision. Though several estimators have been developed for the Weibull function, their application to forestry have been relatively few. Therefore, this study evaluated ten estimators of the Weibull parameters using tree diameter data from five production forest plantations in Nigeria. The estimators were generalized least type I and type II, L-moment, moments, maximum likelihood, percentiles, rank correlation, least squares, U-statistics and weighted least squares. The quality of fits of the Weibull function were evaluated with Kolmogorov-Smirnov, Anderson-Darling, Cramervon Mises, Akaike information criterion and Bayesian information criterion. Relative rank sum from the evaluation statistics of the methods was analysed using One-way analysis of variance. The results showed that weighted least square had the smallest statistics and relative rank, but not significantly different from L-moment, moments and maximum likelihood (p > 0.05). The performances of least squares, generalized least type I and type II, percentiles and U-statistics were relatively poor. Thus, either the weighted least squares, moments-based or MLE could be used for the Weibull function in the diameter distribution of forest stands in Nigeria.

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Bayesian approach for modeling diameter distributions of patula pine (Pinus patula Schiede ex Schltdl. & Cham.) stands in Southern Mexico

Nava-Nava,

Ángeles-Pérez,

Santiago-García

et al. 2024

Trees, Forests and People

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A comparison of estimation methods for fitting Weibull and Johnson’s SB functions to pedunculate oak (Quercus robur) and birch (Betula pubescens) stands in northwest Spain

Cited by 14 publications

References 11 publications

A percentile-based estimator for the log-logistic function: Application to forestry

A percentile-based estimator for the log-logistic function: Application to forestry

An evaluation of ten estimators for fitting two-parameter weibull function to Nigerian forest stands

Bayesian approach for modeling diameter distributions of patula pine (Pinus patula Schiede ex Schltdl. & Cham.) stands in Southern Mexico

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