Author: Stephan Ritter <sritter@berkeley.edu>, Alan Hubbard <hubbard@berkeley.edu>, Nicholas Jewell <jewell@berkeley.edu>
Description: Performs variable importance analysis for possibly many exposures of interest and possibly many outcomes of interest. This is done by fitting Population Intervention Models. The default is to use a Targeted Maximum Likelihood Estimator (TMLE). The other available estimators are Inverse Probability of Censoring Weighted (IPCW), Double-Robust IPCW (DR-IPCW), and Graphical Computation (G-COMP) estimators. Inference can be obtained from the influence curve (plug-in) or by bootstrapping.

Description: Performs variable importance analysis using a causal
inference approach. This is done by fitting Population
Intervention Models. The default is to use a Targeted Maximum
Likelihood Estimator (TMLE). The other available estimators are
Inverse Probability of Censoring Weighted (IPCW), Double-Robust
IPCW (DR-IPCW), and Graphical Computation (G-COMP) estimators.
Inference can be obtained from the influence curve (plug-in) or

Description: Performs variable importance analysis using a causal inference approach. This is done by fitting Population Intervention Models. The default is to use a Targeted Maximum Likelihood Estimator (TMLE). The other available estimators are Inverse Probability of Censoring Weighted (IPCW), Double-Robust IPCW (DR-IPCW), and Graphical Computation (G-COMP) estimators. Inference can be obtained from the influence curve (plug-in) or by bootstrapping.

Title: Multiple Random Dot Product Graphs
Authors@R: c(person("Agnes Martine", "Nielsen", email = "agni@dtu.dk",
role = c("aut", "cre")),person("Daniela", "Witten", role = "aut"))
Description: Fits the Multiple Random Dot Product Graph Model and performs a test
for whether two networks come from the same distribution. Both methods are
proposed in Nielsen, A.M., Witten, D., (2018) "The Multiple Random Dot Product Graph
Model", arXiv preprint <arXiv:1811.12172> (Submitted to Journal of Computational
Author: Agnes Martine Nielsen [aut, cre],
Maintainer: Agnes Martine Nielsen <agni@dtu.dk>