Description: Automate the explanatory analysis of machine learning predictive
models. Generate advanced interactive model explanations in the form of
a serverless HTML site with only one line of code. This tool is
model-agnostic, therefore compatible with most of the black-box predictive
models and frameworks. The main function computes various (instance and
model-level) explanations and produces a customisable dashboard, which
consists of multiple panels for plots with their short descriptions. It is
possible to easily save the dashboard and share it with others. Tools for
Explanatory Model Analysis unite with tools for Exploratory Data Analysis

Title: Estimation of Model-Based Predictions, Contrasts and Means
Description: Implements a general interface for model-based estimations for a wide variety of models (see support list of insight; Lüdecke, Waggoner & Makowski (2019) <doi:10.21105/joss.01412>), used in the computation of marginal means, contrast analysis and predictions.
Imports: insight (>= 0.7.1), bayestestR (>= 0.4.0), parameters (>=
Suggests: coda, covr, dplyr, gganimate, ggplot2, knitr, lme4, MASS,
merTools, rmarkdown, rstanarm, brms, see, testthat

Suggests: coda, covr, dplyr, effectsize, gganimate, ggplot2, knitr,
lme4, MASS, merTools, rmarkdown, rstanarm, brms, see, testthat

0.3.0), emmeans (>= 1.4.4), graphics, stats, utils
Suggests: coda, covr, dplyr, effectsize, gganimate, ggplot2, glmmTMB,
knitr, lme4, logspline, MASS, merTools, mgcv, rmarkdown,

Imports: insight (>= 0.11.0), bayestestR (>= 0.8.0), parameters (>=
0.10.0), emmeans (>= 1.4.4), graphics, stats, utils
Suggests: coda, dplyr, effectsize, gganimate, ggplot2, glmmTMB, knitr,
lme4, Matrix, logspline, MASS, merTools, mgcv, rmarkdown,

Suggests: brms, coda, dplyr, effectsize, gganimate, gamm4, ggplot2,
glmmTMB, knitr, lme4, logspline, Matrix, MASS, merTools, mgcv,

Description: Implements a general interface for model-based
estimations for a wide variety of models (see support list of insight;
Lüdecke, Waggoner & Makowski (2019) <doi:10.21105/joss.01412>), used
in the computation of marginal means, contrast analysis and
Imports: bayestestR (>= 0.8.3), emmeans (>= 1.5.3), graphics, insight
Suggests: brms, coda, dplyr, effectsize, gamm4, gganimate, ggplot2,
glmmTMB, knitr, lme4, logspline, MASS, Matrix, merTools, mgcv,
rmarkdown, rstanarm, see, testthat, spelling