This package implements various measures of information
theory. Several entropy estimators are implemented.

This package implements various measures of information
theory based on several implemented entropy estimators.

This package implements various measures of information
theory based on several entropy estimators.

Orphaned on 2012-12-10 as the orginal maintainer,
Patrick E. Meyer <pmeyer@ulb.ac.be>, is unresponsive.

Implements various measures of information theory based on several entropy estimators.

This package implements various measures of information theory based on several entropy estimators.

Takes a data frame containing latitude and longitude coordinates and downloads images from map servers to determine their file size as a proxy of infrastructure

Facilitates the generation of input files for infraFDTD and processes snapshot output. infraFDTD is a finite-difference model written by Keehoon Kim for simulating infrasound that considers topography and a 1-D atmosphere (see Kim et al., 2015 <doi:10.1002/2015GL064466>).

Replace parameters in strings and/or text files with specified values.

Replace parameters in strings and/or text files with specified
values.

testthat, knitr, rmarkdown, dplyr, magrittr

testthat, knitr, rmarkdown, dbplyr, magrittr

This light-weight templating package provides flexible and
user-friendly value substitution in string templates or template files
(e.g. SQL files) at runtime.

person(given="Kristian", family="Markon", middle="E.", role
= c("aut", "cre"), email = "kristian-markon@uiowa.edu")
Calculation of information utility (i.e., Lindley
information) quantities for item response models.

person(given="Kristian", family="Markon", role = c("aut",
"cre"), email = "kristian-markon@uiowa.edu")

Effects and Importances of Model Ingredients
c(person("Przemyslaw", "Biecek", email = "przemyslaw.biecek@gmail.com",
role = c("aut", "cre"),
comment = c(ORCID = "0000-0001-8423-1823")),
person("Hubert", "Baniecki", role = "ctb"))
Collection of tools for assessment of feature importance and feature effects.
Key functions are:
feature_importance() for assessment of global level feature importance,
ceteris_paribus() for calculation of the what-if plots,
partial_dependency() for partial dependency plots,
conditional_dependency() for conditional dependency plots,
accumulated_dependency() for accumulated local effects plots,
aggregate_profiles() and cluster_profiles() for aggregation of ceteris paribus profiles,
theme_drwhy() with a 'ggplot2' skin for all plots,
generic print() and plot() for better usability of selected explainers.
The package 'ingredients' is a part of the 'DrWhy.AI' universe (Biecek 2018) <arXiv:1806.08915>.
gbm, gower, randomForest, titanic, xgboost, testthat, dplyr,
r2d3, ggpubr, jsonlite
Przemyslaw Biecek [aut, cre] (<https://orcid.org/0000-0001-8423-1823>),
Hubert Baniecki [ctb]