A fully parameterized Generalized Wendland covariance function for use in Gaussian process models, as well as multiple methods for approximating it via covariance interpolation. The available methods are linear interpolation, polynomial interpolation, and cubic spline interpolation.
  Moreno Bevilacqua and Reinhard Furrer and Tarik Faouzi and Emilio Porcu (2019) <url:<https://projecteuclid.org/journalArticle/Download?urlId=10.1214%2F17-AOS1652 >>.
  Moreno Bevilacqua and Christian Caamaño-Carrillo and Emilio Porcu (2022) <arXiv:2008.02904>.
  Reinhard Furrer and Roman Flury and Florian Gerber (2022) <url:<https://CRAN.R-project.org/package=spam >>.

Perform the Blinder-Oaxaca decomposition for generalized linear 
   model with bootstrapped standard errors. The twofold and threefold 
   decomposition are given, even the generalized linear model output in each group.

Allows users to quickly and easily generate fake data containing
    Personally Identifiable Information (PII) through convenience functions.

Generic Machine Learning Inference on heterogeneous treatment effects in randomized experiments as proposed in Chernozhukov, Demirer, Duflo and Fernández-Val (2020) <arXiv:1712.04802>. This package's workhorse is the 'mlr3' framework of Lang et al. (2019) <doi:10.21105/joss.01903>, which enables the specification of a wide variety of machine learners. The main functionality, GenericML(), runs Algorithm 1 in Chernozhukov, Demirer, Duflo and Fernández-Val (2020) <arXiv:1712.04802> for a suite of user-specified machine learners. All steps in the algorithm are customizable via setup functions. Methods for printing and plotting are available for objects returned by GenericML(). Parallel computing is supported.

In order to reduce potential package dependencies and
    conflicts, generics provides a number of commonly used S3 generics.

Estimate gender from names in Spanish and Portuguese. 
    Works with vectors and dataframes. The estimation works not only
    for first names but also full names. The package relies on a
    compilation of common names with it's most frequent associated 
    gender in both languages which are used as look up tables for gender
    inference.