# Fitting and Assessing Neighborhood Models of the Effect of Interspecific Competition on the Growth of Trees

## Documentation for package ‘forestecology’ version 0.2.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

add_buffer_variable | Identify trees in the buffer region
autoplot.comp_bayes_lm | Plot Bayesian model parameters
blocks_ex | Example cross validation grid
census_1_ex | Example input census data for package use
census_2008_bw | Michigan Big Woods research plot data
census_2014_bw | Michigan Big Woods research plot data
census_2_ex | Example input census data for package use
compute_buffer_region | Compute buffer to a region.
compute_growth | Compute growth of trees
comp_bayes_lm | Fit Bayesian competition model
comp_bayes_lm_ex | Example bayesian competition model fit
create_bayes_lm_data | Create input data frame for Bayesian regression
create_focal_vs_comp | Create focal versus competitor trees data frame
focal_vs_comp_distance | Return all pairwise distances between two data frames of trees
focal_vs_comp_ex | Example focal versus comp data frame
forestecology | 'forestecology' package
growth_ex | Example growth data frame for small example
growth_spatial_ex | Example growth data frame with spatial data for small example
growth_toy | Example input data for 'create_focal_vs_comp()'
predict.comp_bayes_lm | Make predictions based on fitted Bayesian model
run_cv | Run the bayesian model with spatial cross validation
species_bw | Phylogenic groupings and trait based clustering of various tree species
study_region_bw | Bigwoods forest study region boundary
study_region_ex | Study region for example data