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Articles containing the keyword 'random parameter'

Category : Article

article id 5563, category Article
Margaret Penner, Hannu Hökkä, Timo Penttilä. (1995). A method for using random parameters in analyzing permanent sample plots. Silva Fennica vol. 29 no. 4 article id 5563. https://doi.org/10.14214/sf.a9214
Keywords: Pinus sylvestris; drained peatlands; drainage; competition; sampling; random parameters
Abstract | View details | Full text in PDF | Author Info

The use of random parameter models in forestry has been proposed as one method of incorporating different levels of information into prediction equations. By explicitly considering the variance-covariance structure of observations and considering some model parameters as random rather than fixed, one can incorporate more complex error structures in analysing data.

Competition indices and variance component techniques were applied to 92 Scots pine (Pinus sylvestris L.) -dominated permanent sample plots on drained peatlands in Northern Finland. By quantifying stand, plot, and tree level variation, it was possible to identify the level (stand, plot or tree) at which the explanatory variables contributed to the model. The replication of plots within stands revealed little variation among plots within a single stand but significant variation occurred at stand and tree levels. Positive and negative effects of inter-tree competition are identified by examining simple correlation statistics and the random parameter model.

  • Penner, E-mail: mp@mm.unknown (email)
  • Hökkä, E-mail: hh@mm.unknown
  • Penttilä, E-mail: tp@mm.unknown

Category : Research article

article id 395, category Research article
Lauri Mehtätalo. (2005). Height-diameter models for Scots pine and birch in Finland. Silva Fennica vol. 39 no. 1 article id 395. https://doi.org/10.14214/sf.395
Keywords: mixed model; longitudinal analysis; random parameter; stand development
Abstract | View details | Full text in PDF | Author Info
Height-Diameter (H-D) models for two shade-intolerant tree species were estimated from longitudinal data. The longitudinal character of the data was taken into account by estimating the models as random effects models using two nested levels: stand and measurement occasion level. The results show that the parameters of the H-D equation develop over time but the development rate varies between stands. Therefore the development of the parameters is not linked to the stand age but to the median diameter of the basal-area weighted diameter distribution (DGM). Models were estimated with different predictor combinations in order to produce appropriate models for different situations. The estimated models can be localized for a new stand using measured heights and diameters, presumably from different points in time, and the H-D curves can be projected into the future.
  • Mehtätalo, Finnish Forest Research Institute, Joensuu Research Centre, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: lauri.mehtatalo@metla.fi (email)

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