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 'iBreakDown' packages). 
    To download the 'LightGBM' use the following link: <https://github.com/Microsoft/LightGBM>.
    'EIX' is a part of the 'DrWhy.AI' universe.

Emissions are the mass of pollutants released into the atmosphere. Air quality models need emissions data, with spatial and temporal distribution, to represent air pollutant concentrations. This package, eixport, creates inputs for the air quality models 'WRF-Chem' Grell et al (2005) <doi:10.1016/j.atmosenv.2005.04.027>, 'MUNICH' Kim et al (2018) <doi:10.5194/gmd-11-611-2018> , 'BRAMS-SPM' Freitas et al (2005) <doi:10.1016/j.atmosenv.2005.07.017> and 'RLINE' Snyder et al (2013) <doi:10.1016/j.atmosenv.2013.05.074>. See the 'eixport' website (<https://atmoschem.github.io/eixport/>) for more information, documentations and examples. More details in Ibarra-Espinosa et al (2018) <doi:10.21105/joss.00607>.

Functions for estimating catalytic constant and Michaelis-Menten constant
            for enzyme kinetics model using Metropolis-Hasting algorithm within Gibbs 
            sampler based on the Bayesian framework.

Extensions of the kernel smoothing functions from the 'ks' package for compatibility with the tidyverse and geospatial ecosystems <doi:10.1007/s00180-024-01543-9>.

Empirical likelihood (EL) inference for two-sample problems.
    The following statistics are included: the difference of two-sample means,
    smooth Huber estimators, quantile (qdiff) and cumulative distribution
    functions (fdiff), probability-probability (P-P) and quantile-quantile
    (Q-Q) plots as well as receiver operating characteristic (ROC) curves.
    Also includes two-sample block-wise empirical likelihood (BEL) and a
    frequency-domain empirical likelihood test for autocorrelation differences
    (FDEL). Methods for EL, P-P, Q-Q, ROC, qdiff and fdiff are based on
    Valeinis and Cers (2011)
    <http://home.lu.lv/~valeinis/lv/petnieciba/EL_TwoSample_2011.pdf>.