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Articles containing the keyword 'seemingly unrelated regression'

Category : Research article

article id 10627, category Research article
Christian Kuehne, J. Paul McLean, Kobra Maleki, Clara Antón-Fernández, Rasmus Astrup. (2022). A stand-level growth and yield model for thinned and unthinned even-aged Scots pine forests in Norway. Silva Fennica vol. 56 no. 1 article id 10627. https://doi.org/10.14214/sf.10627
Keywords: Pinus sylvestris; mortality; volume growth; seemingly unrelated regression; production forestry; system of equations
Highlights: The presented growth and yield model consists of component equations for dominant height, stem density, total basal area, and total stem volume; The component equations were fitted simultaneously using seemingly unrelated regression; The model is capable to forecast and compare outcomes of varying thinning regimes; The new component equations better represent the improved growing conditions for Scots pine in Norway.
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article id 1559, category Research article
Karol Bronisz, Mike Strub, Chris Cieszewski, Szymon Bijak, Agnieszka Bronisz, Robert Tomusiak, Rafał Wojtan, Michał Zasada. (2016). Empirical equations for estimating aboveground biomass of Betula pendula growing on former farmland in central Poland. Silva Fennica vol. 50 no. 4 article id 1559. https://doi.org/10.14214/sf.1559
Keywords: silver birch; simplified and expanded models; seemingly unrelated regression
Highlights: We developed equations for aboveground biomass components of young silver birch stands on post-agricultural lands in central Poland for single tree level; Simplified equations were based exclusively on diameter at ground level or breast height, while expanded ones were based on the appropriate diameter and tree height; For large trees, diameter at breast height is a more appropriate explanatory variable than diameter at ground level; Biomass estimations based on models from neighboring countries were consistent with our results.
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