plotly, zoo, xts, lubridate, RColorBrewer, viridis, scales,
methods, MASS
knitr, rmarkdown, devtools, BiocStyle, dbscan

Functions to delineate temporal dataset shifts in Electronic Health
Records through the projection and visualization of dissimilarities
among data temporal batches. This is done through the estimation of
data statistical distributions over time and their projection in
non-parametric statistical manifolds, uncovering the patterns of the
data latent temporal variability. 'EHRtemporalVariability' is
particularly suitable for multi-modal data and categorical variables
with a high number of values, common features of biomedical data where
traditional statistical process control or time-series methods may not
be appropriate. 'EHRtemporalVariability' allows you to explore and
identify dataset shifts through visual analytics formats such as
Data Temporal heatmaps and Information Geometric Temporal (IGT) plots.
An additional 'EHRtemporalVariability' Shiny app can be used to load
and explore the package results and even to allow the use of these
functions to those users non-experienced in R coding. (Sáez et al. 2020)
<doi:10.1093/gigascience/giaa079>.
knitr, rmarkdown, devtools, BiocStyle, dbscan, webshot

R Wrapper for the Energy Information Administration (EIA) API
An R wrapper to allow the user to query categories and Series IDs, and import data, from the EIA's API.

An R wrapper to allow the user to query categories and Series IDs, and import data, from the EIA's API <https://www.eia.gov/opendata/>.

Implementation of Efficient Inference of Local Ancestry
using fused quantile regression and k-means classifier

James J. Yang, Jia Li, Anne Buu, and L. Keoki Williams

c(
person("Ewelina", "Karbowiak", email = "ewelina.karbowiak12@gmail.com", role = c("aut", "cre")),
person("Przemyslaw", "Biecek", email = "przemyslaw.biecek@gmail.com", role = c("aut","ths"))
)
Structure mining from 'XGBoost' and 'LightGBM' models.
Key functionalities of this package cover: visualisation of tree-based ensembles models,
identification of interactions, measuring of variable importance,
measuring of interaction importance, explanation of single prediction
with break down plots (based on 'xgboostExplainer' and 'breakDown' packages).
To download the 'LightGBM' use the following link: <https://github.com/Microsoft/LightGBM>.
'EIX' is a part of the 'DrWhy.AI' universe.
MASS, ggplot2, data.table, purrr, xgboost, DALEX, ggrepel,
ggiraphExtra, iBreakDown, Matrix, tidyr, scales
Ewelina Karbowiak [aut, cre],
Przemyslaw Biecek [aut, ths]