distreg.vis: distreg.vis: Interactively visualizing distributional...
In distreg.vis: Framework for the Visualization of Distributional Regression Models

distreg.vis

R Documentation

distreg.vis: Interactively visualizing distributional regression models

Description

The package distreg.vis is a framework for the visualization of distributional regression models estimated with the R packages bamlss, gamlss and betareg. Current supported model classes can be found under distreg_checker.

Details

The main functions are:

vis(): Starts the Graphical User Interface.
moments(): Obtain predicted moments of the target distribution based on user-specified values of the explanatory variables.
plot_dist(): Create a graph displaying the predicted probability density function or cumulative density function based on the same user-specified values.
plot_moments(): View the marginal influence of a selected effect on the predicted moments of the target distribution.

To get a feel for the main capabilities of distreg.vis, you can run the examples or the demo called vis-demo.R which fits a couple of distributional regression models and then calls the Graphical User Interface.

For the main functions, certain target distributions from both bamlss and gamlss are supported. Check the distreg.vis::dists dataset to find out which distributions are supported for plot_dist() (column implemented) and which are also supported for plot_moments() (column moment_funs).

To make the process of interpreting fitted distributional regression models as easy as possible, distreg.vis features a rich Graphical User Interface (GUI) built on the shiny framework. Using this GUI, the user can (a) obtain an overview of the selected model fit, (b) easily select explanatory values for which to display the predicted distributions, (c) obtain marginal influences of selected covariates and (d) change aesthetical components of each displayed graph. After a successful analysis, the user can quickly obtain the R code needed to reproduce all displayed plots, without having to start the application again.

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