multiviewtest-package: multiviewtest: Hypothesis tests for association between...
In multiviewtest: Hypothesis Tests for Association Between Subgroups in Two Data Views
Description
Details
Dependencies
multiviewtest functions
Description
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
Details
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.
Dependencies
mclust (>= 5.3), matrixStats (>= 0.52.2), Matrix, randnet, doParallel, irbla
multiviewtest functions
test_indep_clust: Tests whether clusterings of two multivariate data views are independent.
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.
test_indep_com: Tests whether communities in two network data views are independent.
test_indep_com_clust: Test whether communities in a network data view and clusters in a
multivariate data view are independent.
optimize_over_pi_clust: An optimization algorithm used in the test of whether clusterings
of two data views are independent.
mv_memberships_gen: Generates subgroup memberships in two data views.
mv_gmm_gen: Generates two multivariate data views, where each view follows a Gaussian mixture model.
mv_sbm_gen: Generates two network data views, where each view follows a stochastic block model.
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.
multiviewtest documentation built on Oct. 13, 2021, 5:08 p.m.
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Description Details Dependencies multiviewtest functions
Description
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
Details
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.
Dependencies
mclust (>= 5.3), matrixStats (>= 0.52.2), Matrix, randnet, doParallel, irbla
multiviewtest functions
test_indep_clust: Tests whether clusterings of two multivariate data views are independent.
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.
test_indep_com: Tests whether communities in two network data views are independent.
test_indep_com_clust: Test whether communities in a network data view and clusters in a
multivariate data view are independent.
optimize_over_pi_clust: An optimization algorithm used in the test of whether clusterings
of two data views are independent.
mv_memberships_gen: Generates subgroup memberships in two data views.
mv_gmm_gen: Generates two multivariate data views, where each view follows a Gaussian mixture model.
mv_sbm_gen: Generates two network data views, where each view follows a stochastic block model.
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.
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