Ternary Plots for Trinomial Regression Models
It adds the confidence regions to a "field3logit" object
Compute the confidence regions of covariate effects
Create a gg3logit plot with field and confidence regions
It computes the confidence region in the ternary space
Computes convex combinations of two vectors
Identification of equispaced central points
Identification of roles of vertices in non-degenerate cases
Draw a change in the probability distribution on an existing plot
Extract information from fitted models
Computation of the vector field
Generates a curve of the field
It computes the vector of covariate change
Create a new gg3logit
Set the labels of a field3logit or a multifield3logit object
Compute the linear predictors implied by trinomial probability distrib...
Computes trinomial probability distributions implied by linear predict...
Multiple trilogit fields
Computation of starting points of curves of the field
Ternary Plots for Trinomial Regression Models
Objects exported from other packages
field3logit simplification function and test
Add a field and confidence regions to a gg3logit plot
Add the confidence regions of a field to a gg3logit plot
Add a field to a gg3logit plot
Convert a tibble to a matrix
Draw a field on an existing ternary plot
Computes the coordinates of a vertex on the edge
Covariance matrix of covariate change
Computes the versor
An implementation of the ternary plot for interpreting regression coefficients of trinomial regression models, as proposed in Santi, Dickson and Espa (2019) <doi:10.1080/00031305.2018.1442368>. Ternary plots can be drawn using either 'ggtern' package (based on 'ggplot2') or 'Ternary' package (based on standard graphics). The package and its features are illustrated in Santi, Dickson, Espa and Giuliani (2022) <doi:10.18637/jss.v103.c01>.
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