Ontology highlight
ABSTRACT:
SUBMITTER: Frot B
PROVIDER: S-EPMC6636895 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
Frot Benjamin B Jostins Luke L McVean Gilean G
Journal of the American Statistical Association 20180711 526
We consider the problem of learning a conditional Gaussian graphical model in the presence of latent variables. Building on recent advances in this field, we suggest a method that decomposes the parameters of a conditional Markov random field into the sum of a sparse and a low-rank matrix. We derive convergence bounds for this estimator and show that it is well-behaved in the high-dimensional regime as well as "sparsistent" (i.e., capable of recovering the graph structure). We then show how prox ...[more]