Title: Implements the Forest-R.K. Algorithm for Classification Problems
Description: Provides functions that calculates common types of splitting
criteria used in random forests for classification problems, as well as
functions that make predictions based on a single tree or a Forest-R.K. model;
the package also provides functions to generate importance plot for a
Forest-R.K. model, as well as the 2D multidimensional-scaling plot of
data points that are colour coded by their predicted class types by the
Forest-R.K. model. This package is based on:
"Forest-R.K.: A New Random Forest Induction Method",
Fourth International Conference on Intelligent Computing,
September 2008, Shanghai, China, pp.430-437.
person("Hyunjin", "Cho", email = "h56cho@uwaterloo.ca", role = c("aut","cre")),
person("Rebecca", "Su", email = "y57su@uwaterloo.ca", role = "ctb"))
Imports: igraph, ggplot2, rapportools, partykit, stats, graphics,
Note: The package is also based on the discussion
Packaged: 2019-07-18 17:33:49 UTC; jin-dominique

Title: Forest Spatial Structure Analysis Systems
Description: In recent years, there has been considerable interest in a group of neighborhood-based structural parameters that properly express the spatial structure characteristics of tree populations and forest communities and have strong operability for guiding forestry practices.the 'forestSAS' package provide more important information and allow us to better understand and analyze the fine-scale spatial structure of tree populations and stand structure.
Packaged: 2019-01-02 13:28:52 UTC; Administrator

Title: Methods and Data for Forest Ecology Model Fitting and Assessment
person(given = "Albert Y.", family = "Kim", email = "albert.ys.kim@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-7824-306X")),
person(given = "David", family = "Allen", email = "dallen@middlebury.edu", role = "aut", comment = c(ORCID = "0000-0002-0712-9603")),
person(given = "Simon", family = "Couch", email = "simonpatrickcouch@gmail.com", role = "aut", comment = c(ORCID = "0000-0001-5676-5107"))
Description: Code for fitting and assessing models for the growth of trees. In
particular for the Bayesian neighborhood competition linear regression model
of Allen (2020): methods for model fitting and generating fitted/predicted
values, evaluating the effect of competitor species identity using
permutation tests, and evaluating model performance using spatial
Imports: magrittr, rlang, glue, ggplot2, stringr, dplyr, tidyr, proxy,
purrr, ggridges, mvnfast, sf, sfheaders, snakecase, tibble,