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.

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.

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.science/hal-00714174/>) ; S. Karlin and S. Altschul (1990) <https://pmc.ncbi.nlm.nih.gov/articles/PMC53667/>  ; S. Mercier, D. Cellier and F. Charlot (2003) <https://hal.science/hal-00937529v1/> ; A. Lagnoux, S. Mercier and P. Valois (2017) <doi:10.1093/bioinformatics/btw699> ).

The package converts R data onto input and data for LocalSolver,
    executes optimization and exposes optimization results as R data.
    LocalSolver (http://www.localsolver.com/) is an optimization engine
    developed by Innovation24 (http://www.innovation24.fr/). It is designed to
    solve large-scale mixed-variable non-convex optimization problems.  The
    localsolver package is developed and maintained by WLOG Solutions
    (http://www.wlogsolutions.com/en/) in collaboration with Decision Support
    and Analysis Division at Warsaw School of Economics
    (http://www.sgh.waw.pl/en/).