Visualising and Interpreting Statistical Models Fit to Compositional Data
Add additional variables to data via cartesian product
Add predictions and uncertainty interval to data using either a model ...
Data preparation for conditional ternary diagrams
Conditional ternary diagrams
DI specific wrapper for conditional ternary diagrams
Copy attributes from one object to another
Special custom filtering for compositional data
Add identity and interaction terms used in a Diversity-Interactions (D...
DImodelsVis: Model interpretation and visualisation for compositional ...
Return colour-blind friendly colours
Get all equi-proportional communities at specific levels of richness
Returns shades of colours
Data preparation for visualising change in response over diversity gra...
Visualise change in response over diversity gradient
DI specific wrapper for visualising change in response over diversity ...
Combine variable proportions into groups
Prepare data for grouped ternary diagrams
Grouped ternary diagrams
DI specific wrapper for grouped ternary diagrams
Data preparation of diagnostics plots for regression models with compo...
Diagnostics plots for regression models with compositional predictors
DI specific wrapper of diagnostics plots for regression models with co...
Prepare data for visualising model selection
Visualise model selection
DI specific wrapper for visualising model selection
Model term contributions to predicted response
Visualise model term contributions to predicted response
Model term contributions to predicted response
Prepare data for visualising change in response across points in the s...
Visualising change in response across points in the simplex space
DI specific for visualising change in response across points in the si...
Project 3-d compositional data onto x-y plane and vice versa
Prepare data for showing contours in ternary diagrams.
Ternary diagrams
Default theme for DImodelsVis
Prepare data for effects plots of compositional predictors
Effects plot for compositional predictors
DI specific wrapper of effects plot for compositional variables
Statistical models fit to compositional data are often difficult to interpret due to the sum to 1 constraint on data variables. 'DImodelsVis' provides novel visualisations tools to aid with the interpretation of models fit to compositional data. All visualisations in the package are created using the 'ggplot2' plotting framework and can be extended like every other 'ggplot' object.