NEWS

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forestecology 0.2.0.9000

forestecology 0.2.0 (2021-10-02)

• Added Ecology & Evolution paper to paper/ https://doi.org/10.1002/ece3.8129
• Made choice of competitor explanatory variable more flexible by adding create_focal_vs_comp(comp_x_var = ...) argument.

forestecology 0.1.0 (2021-03-12)

• Switched CI from travis to GitHub actions
• Refactored spatial cross-validation in run_cv() to use purrr::map_dfr() using the fit_one_fold() function
• Transition modeling, prediction, and plotting functions from generics to S3 methods for the comp_bayes_lm class.
• Aligned inputs and outputs of modeling and prediction functions with S3 modeling conventions and tidy data principles. Namely,
  • The comp_bayes_lm() modeling function takes in a data frame at a level of observation equivalent to that which the model is actually fit to: each row is a unique focal observation/tree rather than focal-competitor observation pairs/trees. The function outputs a model object with several associated modeling S3 methods.
  • predict.comp_bayes_lm() takes in a model object as its first argument and input data as its second argument. The output, an unnamed vector, has length equal to the input data.
• Added argument checks.