R: Visualising and Interpreting Statistical Models Fit to Compositional Data

# Visualising and Interpreting Statistical Models Fit to Compositional Data

## Documentation for package ‘DImodelsVis’ version 1.0.4

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

add_add_var | Add additional variables to data via cartesian product
add_ID_terms | Add identity and interaction terms used in a Diversity-Interactions (DI) model to new data
add_interaction_terms | Add identity and interaction terms used in a Diversity-Interactions (DI) model to new data
add_prediction | Add predictions and uncertainty interval to data using either a model object or model coefficients.
conditional_ternary | DI specific wrapper for conditional ternary diagrams
conditional_ternary_data | Data preparation for conditional ternary diagrams
conditional_ternary_plot | Conditional ternary diagrams
copy_attributes | Copy attributes from one object to another
custom_filter | Special custom filtering for compositional data
get_colours | Return colour-blind friendly colours
get_equi_comms | Get all equi-proportional communities at specific levels of richness
get_shades | Returns shades of colours
gradient_change | DI specific wrapper for visualising change in response over diversity gradient
gradient_change_data | Data preparation for visualising change in response over diversity gradient
gradient_change_plot | Visualise change in response over diversity gradient
grouped_ternary | DI specific wrapper for grouped ternary diagrams
grouped_ternary_data | Prepare data for grouped ternary diagrams
grouped_ternary_plot | Grouped ternary diagrams
group_prop | Combine variable proportions into groups
model_diagnostics | DI specific wrapper of diagnostics plots for regression models with compositional predictors
model_diagnostics_data | Data preparation of diagnostics plots for regression models with compositional predictors
model_diagnostics_plot | Diagnostics plots for regression models with compositional predictors
model_selection | DI specific wrapper for visualising model selection
model_selection_data | Prepare data for visualising model selection
model_selection_plot | Visualise model selection
prediction_contributions | Model term contributions to predicted response
prediction_contributions_data | Model term contributions to predicted response
prediction_contributions_plot | Visualise model term contributions to predicted response
prop_to_tern_proj | Project 3-d compositional data onto x-y plane and vice versa
simplex_path | DI specific for visualising change in response across points in the simplex space
simplex_path_data | Prepare data for visualising change in response across points in the simplex space
simplex_path_plot | Visualising change in response across points in the simplex space
ternary_data | Prepare data for showing contours in ternary diagrams.
ternary_plot | Ternary diagrams
tern_to_prop_proj | Project 3-d compositional data onto x-y plane and vice versa
theme_DI | Default theme for DImodelsVis
visualise_effects | DI specific wrapper of effects plot for compositional variables
visualise_effects_data | Prepare data for effects plots of compositional predictors
visualise_effects_plot | Effects plot for compositional predictors