This package contains code, help and examples for Estimation of Diagonal Elements of Sparse Precision-Matrices, as described in "On estimation of the diagonal elements of a sparse precision matrix" by Samuel Balmand and Arnak S. Dalalyan (posted as http://arxiv.org/abs/1504.04696).

Contributors:

Arnak Dalalyan <Arnak.Dalalyan@ensae.fr>
Samuel Balmand <Samuel.Balmand@ensg.eu>

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This package contains the following methods:

   DESP_MST 		Estimation of DESP using minimum spanning trees
   DESP_PML 		Estimation of DESP by penalized likelihood minimization
   DESP_RML 		Estimation of DESP by likelihood maximization
   DESP_RV 		Estimation of DESP by residual variance
   DESP_SPT 		Estimation of DESP using shortest path trees
   DESP_SRL_B 		Estimation of the coefficient matrix
   sqR_Lasso		Solve the square-root LASSO
   scsSOCP		Solve a second-order cone program using SCS

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Requirements:

The open source solver SCS is already available in this package (see https://github.com/cvxgrp/scs), but to use the convex optimization proprietary software MOSEK or GUROBI that have an R interface, one has to install them separately.

For estimating the coefficient matrix with the square-root Lasso with the MOSEK solver, DESP needs a working version of the Rmosek package that requires MOSEK and a MOSEK license (see http://rmosek.r-forge.r-project.org/).

For estimating the coefficient matrix with the square-root Lasso with the GUROBI solver, DESP needs a working version of the gurobi package that requires GUROBI and a GUROBI license (see http://www.gurobi.com/documentation/6.0/refman/r_api_overview.html).
