R/multiviewtest.R

In multiviewtest: Hypothesis Tests for Association Between Subgroups in Two Data Views

#' multiviewtest: Hypothesis tests for association between subgroups in two data views.
#'
#' The multiviewtest package implements three tests for association between subgroups in 
#' two data views: 
#' 1. The PLRT for association between clusterings of two multivariate data views
#' 2. The P2LRT for association between communities in two network data views
#' 3. The P2LRT for association between communities in a network view, 
#' and clusters in a multivariate data view
#' 
#' The PLRT was proposed in Gao, Bien, and Witten (2019) Are Clusterings of 
#' Multiple Data Views Independent? Biostatistics, DOI: 10.1093/biostatistics/kxz001. 
#' 
#' The P2LRT was proposed in Gao, Witten, Bien (2019+) Testing for Association 
#' in Multi-View Network Data, in preparation. 
#'
#' @section Dependencies: mclust (>= 5.3), matrixStats (>= 0.52.2), Matrix, randnet, doParallel, irbla
#'
#' @section multiviewtest functions:
#' \code{test_indep_clust}: Tests whether clusterings of two multivariate data views are independent.
#' \code{test_indep_clust_subset}: Tests whether clusterings of two multivariate data views are independent,
#' allowing for clustering on the full data views and comparing on subsets of the data views.
#' \code{test_indep_com}: Tests whether communities in two network data views are independent. 
#' \code{test_indep_com_clust}: Test whether communities in a network data view and clusters in a 
#' multivariate data view are independent.
#' \code{optimize_over_pi_clust}: An optimization algorithm used in the test of whether clusterings
#' of two data views are independent.
#' \code{mv_memberships_gen}: Generates subgroup memberships in two data views. 
#' \code{mv_gmm_gen}: Generates two multivariate data views, where each view follows a Gaussian mixture model. 
#' \code{mv_sbm_gen}: Generates two network data views, where each view follows a stochastic block model. 
#' \code{mv_sbm_gmm_gen}: Generates a network view and a multivariate view, where the network view follows
#' a stochastic block model and the multivariate view follows a Gaussian mixture model. 
#'
#'
#' @docType package
#' @name multiviewtest-package
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