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WoodSimulatR

The WoodSimulatR package has been developed in the project InnoGrading by Holzforschung Austria (https://www.holzforschung.at).

It provides tools for generating simulated sawn timber strength grading data.

The main focus is statistical simulation based on covariance matrices.

WoodSimulatR also contains pre-stored simulation data for Norway spruce (Picea abies) sawn timber from Austria and reference values of means and standard deviations of grade determining properties (GDPs) from literature for a number of European countries.

Installation

You can install the released version of WoodSimulatR from CRAN with:

install.packages("WoodSimulatR")

Vignette

The most important use cases are explained in the vignette woodsimulatr_basics which can be accessed by:

vignette('woodsimulatr_basics', package = 'WoodSimulatR')

Acknowledgements

The project InnoGrading was funded by the Austrian Research Promotion Agency (FFG; project nr. 869170).

The package WoodSimulatR was inspired by the work of Ranta-Maunus and Turk (2010).

References

Ranta-Maunus, Alpo, and Goran Turk. 2010. “Approach of Dynamic Production Settings for Machine Strength Grading.” In 11th World Conference on Timber Engineering 2010 (WCTE 2010), edited by A. Ceccotti and Jan-Willem G. van de Kuilen.

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Version

Install

install.packages('WoodSimulatR')

Monthly Downloads

178

Version

0.6.2

License

MIT + file LICENSE

Maintainer

Andreas Weidenhiller

Last Published

March 3rd, 2025

Functions in WoodSimulatR (0.6.2)

simbase_list

Wrapper for the simbase_* functions for grouped data
simulate_dataset

Generate an artificial dataset with correlated variables
simulate_conditionally

Add simulated values to a dataset conditionally, based on a simbase_* object
gdp_data

Means and standard deviations of grade determining properties (GDPs) from literature
simbase

Predefined simbases in WoodSimulatR
get_subsample_definitions

Retrieve descriptive data for samples from literature
simbase_labeler

Default labelling function for simbase objects
simulate_conditionally.simbase_list

Add simulated values to a dataset conditionally, based on a simbase_list object
simbase_covar

Calculate reference data for simulating values based on a covariance matrix approach
get_transform_names

Return labels for given transforms