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DESCRIPTION
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DESCRIPTION
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Package: FactorHet
Title: Estimate Heterogeneous Effects in Factorial Experiments Using Clustering and Sparsity
Version: 0.0.0.1
Author: Max Goplerud <mgoplerud@pitt.edu>, Kosuke Imai <imai@harvard.edu>, Nicole E. Pashley <nicole.pashley@rutgers.edu>
Maintainer: Max Goplerud <mgoplerud@pitt.edu>
Description: This package faciliates the estimation of heterogeneous effects in factorial (and conjoint) models. Its details are fully described in Goplerud, Imai, and Pashley (2022) <doi:10.48550/ARXIV.2201.01357>. The methodology employs a Bayesian finite mixture of regularized logistic experts, where moderators can affect each observation's probability of cluster membership and a sparsity-inducing prior fuses together levels of each factor while respecting ANOVA-style sum-to-zero constraints.
Depends: R (>= 3.4.0)
License: GPL (>= 2)
Encoding: UTF-8
RoxygenNote: 7.1.2
LinkingTo: Rcpp, RcppEigen
Imports: Rcpp (>= 1.0.1), RcppEigen (>= 0.3.3.4.0), Matrix,
rlang, ggplot2, reshape2, methods,
ParamHelpers, dplyr, mlr, mlrMBO, smoof, tictoc
Suggests:
FNN, RSpectra, mclust,
tgp, testthat,
LazyData: true