Title: Fully Parameterized Generalized Wendland Covariance Function
person(c("Thomas", "C."), "Fischer", role = c("aut", "cre"), email = "thomascasparfischer@gmail.com"),
person("Reinhard", "Furrer", role = c("aut", "ths"), email = "reinhard.furrer@math.uzh.ch"),
person("Josef", "Stocker", role = c("aut"), email = "josef.stocker@posteo.ch"))
Maintainer: Thomas C. Fischer <thomascasparfischer@gmail.com>
Imports: methods, stats, utils, Matrix, Rcpp, spam, spam64, parallel,
Suggests: knitr, R.rsp, testthat (>= 3.0.0), mvtnorm, ggplot2,
Description: 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 >>.

Title: Generic Machine Learning Inference
Description: 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.
Imports: sandwich, lmtest, splitstackshape, stats, parallel
Suggests: glmnet, ranger, rpart, e1071, testthat (>= 3.0.0)