In the generalized Roy model, the marginal treatment effect (MTE) can be used as
a building block for constructing conventional causal parameters such as the average treatment
effect (ATE) and the average treatment effect on the treated (ATT). Given a treatment selection
equation and an outcome equation, the function mte() estimates the MTE via the semiparametric
local instrumental variables method or the normal selection model. The function mte_at() evaluates
MTE at different values of the latent resistance u with a given X = x, and the function mte_tilde_at()
evaluates MTE projected onto the estimated propensity score. The function ace() estimates
population-level average causal effects such as ATE, ATT, or the marginal policy relevant
treatment effect.

LIME-Based Explanations with Interpretable Inputs Based on
Ceteris Paribus Profiles
Mateusz Staniak [aut, cre],
Przemyslaw Biecek [aut],
Krystian Igras [ctb],
Alicja Gosiewska [ctb]
Local explanations of machine learning models describe, how features contributed to a single prediction.
This package implements an explanation method based on LIME
(Local Interpretable Model-agnostic Explanations,
see Tulio Ribeiro, Singh, Guestrin (2016) <doi:10.1145/2939672.2939778>) in which interpretable
inputs are created based on local rather than global behaviour of each original feature.
covr, knitr, rmarkdown, randomForest, DALEX, testthat

c(person("Przemyslaw", "Biecek", email = "przemyslaw.biecek@gmail.com", role = c("aut", "cre")),
person("Mateusz", "Staniak", role = "aut"),
person("Krystian", "Igras", role = "ctb"),
person("Alicja", "Gosiewska", role = "ctb"),
person("Harel", "Lustiger", role = "ctb"),
person("Willy", "Tadema", role = "ctb")
)
glmnet, DALEX, ggplot2, partykit, ingredients
covr, knitr, rmarkdown, randomForest, testthat
Przemyslaw Biecek [aut, cre],
Mateusz Staniak [aut],
Krystian Igras [ctb],
Alicja Gosiewska [ctb],
Harel Lustiger [ctb],
Willy Tadema [ctb]

Package for Sequence Analysis by Local Score
c(person("Sebastian", "Simon", role = "aut"),
person("David", "Robelin", role = c("aut","cre"),
email = "david.robelin@inrae.fr"),
person("Sabine", "Mercier", role = "aut",
email = "sabine.mercier@univ-tlse2.fr"),
person("Sebastien", "Dejean", role = "aut",
email="sebastien.dejean@math.univ-toulouse.fr"),
person(given="The authors of Eigen the library for the included version of Eigen", role = "cph"))
See the file COPYRIGHTS for various embedded Eigen library
copyright details
Functionalities for calculating the local score and calculating statistical relevance (p-value) to find a local Score in a sequence of given distribution (S. Mercier and J.-J. Daudin (2001) <https://hal.archives-ouvertes.fr/hal-00714174> ; S. Karlin and S. Altschul (1990) <https://www.pnas.org/content/87/6/2264> ; S. Mercier, D. Cellier and F. Charlot (2003) <https://hal.archives-ouvertes.fr/hal-00937529v1> ; A. Lagnoux, S. Mercier and P. Valois (2017) <doi:10.1093/bioinformatics/btw699> ).
Sebastian Simon [aut],
David Robelin [aut, cre],
Sabine Mercier [aut],
Sebastien Dejean [aut],
The authors of Eigen the library for the included version of Eigen
[cph]