The main function, plot_mm(), is used for (gg)plotting output from mixture models,
including both densities and overlaying mixture weight component curves from the fit models in line with the
tidy principles. The package includes several additional functions for added plot customization.
Supported model objects include: 'mixtools', 'EMCluster', and 'flexmix', with more from each in active dev.
Supported mixture model specifications include mixtures of univariate Gaussians, multivariate Gaussians, Gammas,
logistic regressions, linear regressions, and Poisson regressions.
mixtools, EMCluster, flexmix, testthat, graphics, dplyr,
patchwork, magrittr, knitr, rmarkdown

Plot a model's response while varying the values of the
predictors.
Plot a model's response when varying one or two predictors
while holding the other predictors constant.  A poor man's
partial dependence plot.

Plot a Model's Response While Varying the Values of the
Predictors

Plot a model's response when varying one or two predictors
while holding the other predictors constant.  A poor man's
partial dependence plot.  Also plot model residuals.
earth (>= 4.2.0), MASS, neuralnet, rpart, rpart.plot

earth (>= 4.3.0), MASS, neuralnet, rpart, rpart.plot

Plot a model's response when varying one or two predictors
while holding the other predictors constant.  A poor man's
partial dependence plot.  Also plot model residuals and other
information on the model.

Plot model surfaces for a wide variety of models
using partial dependence plots and other techniques.
Also plots model residuals and other information on the model.

Plot model surfaces for a wide variety of models
using partial dependence plots and other techniques.
Also plot model residuals and other information on the model.

Plot a Model's Residuals, Response, and Partial Dependence Plots

R (>= 3.2.0), Formula (>= 1.2-3), plotrix, TeachingDemos

R (>= 3.4.0), Formula (>= 1.2-3), plotrix, TeachingDemos

Plot principal component histograms around a scatter plot.
Plot principal component histograms around a bivariate scatter plot.