% JoÃ«lle Skaf - 04/24/08
% (a figure is generated)
%
% Suppose y \in\reals^n is a Gaussian random variable with zero mean and
% covariance matrix R = \Expect(yy^T), with sparse inverse S = R^{-1}
% (S_ij = 0 means that y_i and y_j are conditionally independent).
% We want to estimate the covariance matrix R based on N independent
% samples y1,...,yN drawn from the distribution, and using prior knowledge
% that S is sparse
% A good heuristic for estimating R is to solve the problem
%           maximize    logdet(S) - tr(SY)
%           subject to  sum(sum(abs(S))) <= alpha
%                       S >= 0
% where Y is the sample covariance of y1,...,yN, and alpha is a sparsity
% parameter to be chosen or tuned.

% Input data
rand('state',0);
randn('state',0);
n = 10;
N = 100;
Strue = sprandsym(n,0.5,0.01,1);
R = inv(full(Strue));
y_sample = sqrtm(R)*randn(n,N);
Y = cov(y_sample');
alpha = 50;

% Computing sparse estimate of R^{-1}
cvx_begin sdp
variable S(n,n) symmetric
maximize log_det(S) - trace(S*Y)
sum(sum(abs(S))) <= alpha
S >= 0
cvx_end
R_hat = inv(S);

S(find(S<1e-4)) = 0;
figure;
subplot(121);
spy(Strue);
title('Inverse of true covariance matrix')
subplot(122);
spy(S)
title('Inverse of estimated covariance matrix')


Calling Mosek 9.1.9: 503 variables, 223 equality constraints
For improved efficiency, Mosek is solving the dual problem.
------------------------------------------------------------

MOSEK Version 9.1.9 (Build date: 2019-11-21 11:32:15)
Copyright (c) MOSEK ApS, Denmark. WWW: mosek.com
Platform: MACOSX/64-X86

Problem
Name                   :
Objective sense        : min
Type                   : CONIC (conic optimization problem)
Constraints            : 223
Cones                  : 112
Scalar variables       : 238
Matrix variables       : 2
Integer variables      : 0

Optimizer started.
Presolve started.
Linear dependency checker started.
Linear dependency checker terminated.
Eliminator started.
Freed constraints in eliminator : 1
Eliminator terminated.
Eliminator started.
Freed constraints in eliminator : 0
Eliminator terminated.
Eliminator - tries                  : 2                 time                   : 0.00
Lin. dep.  - tries                  : 1                 time                   : 0.00
Lin. dep.  - number                 : 0
Presolve terminated. Time: 0.00
Problem
Name                   :
Objective sense        : min
Type                   : CONIC (conic optimization problem)
Constraints            : 223
Cones                  : 112
Scalar variables       : 238
Matrix variables       : 2
Integer variables      : 0

Optimizer  - threads                : 8
Optimizer  - solved problem         : the primal
Optimizer  - Constraints            : 220
Optimizer  - Cones                  : 112
Optimizer  - Scalar variables       : 236               conic                  : 236
Optimizer  - Semi-definite variables: 2                 scalarized             : 265
Factor     - setup time             : 0.00              dense det. time        : 0.00
Factor     - ML order time          : 0.00              GP order time          : 0.00
Factor     - nonzeros before factor : 1.13e+04          after factor           : 1.51e+04
Factor     - dense dim.             : 0                 flops                  : 1.37e+06
ITE PFEAS    DFEAS    GFEAS    PRSTATUS   POBJ              DOBJ              MU       TIME
0   6.1e+01  4.9e+01  6.0e+01  0.00e+00   5.082783840e+01   -8.051020016e+00  1.0e+00  0.01
1   2.1e+01  1.7e+01  3.0e+01  -8.79e-01  1.217303462e+02   7.326525751e+01   3.4e-01  0.01
2   1.1e+01  8.7e+00  1.0e+01  -1.15e-01  8.231499201e+01   5.583913632e+01   1.8e-01  0.01
3   7.7e+00  6.2e+00  6.1e+00  8.43e-01   5.277890064e+01   3.414156858e+01   1.3e-01  0.02
4   3.6e+00  2.9e+00  1.8e+00  9.69e-01   1.781699073e+01   9.473958843e+00   6.0e-02  0.02
5   3.1e+00  2.5e+00  1.7e+00  7.34e-01   1.410839818e+01   5.922417259e+00   5.2e-02  0.02
6   1.3e+00  1.1e+00  4.6e-01  9.57e-01   -2.791851684e+00  -6.195477449e+00  2.2e-02  0.02
7   9.7e-01  7.8e-01  3.8e-01  5.16e-01   -7.183712277e+00  -1.047247820e+01  1.6e-02  0.02
8   3.4e-01  2.7e-01  8.1e-02  8.82e-01   -1.713503096e+01  -1.831741253e+01  5.6e-03  0.02
9   2.0e-01  1.6e-01  4.9e-02  3.98e-01   -2.091268740e+01  -2.184632115e+01  3.3e-03  0.03
10  1.1e-01  8.7e-02  2.2e-02  6.17e-01   -2.432696249e+01  -2.489972434e+01  1.8e-03  0.03
11  3.9e-02  3.1e-02  5.5e-03  7.24e-01   -2.806687910e+01  -2.829261309e+01  6.3e-04  0.03
12  1.8e-02  1.4e-02  1.9e-03  8.04e-01   -2.961876411e+01  -2.972995868e+01  2.9e-04  0.03
13  1.8e-03  1.5e-03  6.5e-05  9.29e-01   -3.105635218e+01  -3.106814847e+01  3.0e-05  0.03
14  8.5e-05  6.8e-05  6.6e-07  9.88e-01   -3.123140897e+01  -3.123195670e+01  1.4e-06  0.03
15  1.4e-06  1.1e-06  1.3e-09  9.99e-01   -3.123991549e+01  -3.123992431e+01  2.2e-08  0.04
16  5.7e-08  4.6e-08  1.2e-11  1.00e+00   -3.124004920e+01  -3.124004957e+01  9.4e-10  0.04
Optimizer terminated. Time: 0.04

Interior-point solution summary
Problem status  : PRIMAL_AND_DUAL_FEASIBLE
Solution status : OPTIMAL
Primal.  obj: -3.1240049204e+01   nrm: 2e+02    Viol.  con: 4e-07    var: 0e+00    barvar: 0e+00    cones: 0e+00
Dual.    obj: -3.1240049573e+01   nrm: 2e+00    Viol.  con: 0e+00    var: 3e-07    barvar: 7e-09    cones: 0e+00
Optimizer summary
Optimizer                 -                        time: 0.04
Interior-point          - iterations : 16        time: 0.04
Basis identification  -                        time: 0.00
Primal              - iterations : 0         time: 0.00
Dual                - iterations : 0         time: 0.00
Clean primal        - iterations : 0         time: 0.00
Clean dual          - iterations : 0         time: 0.00
Simplex                 -                        time: 0.00
Primal simplex        - iterations : 0         time: 0.00
Dual simplex          - iterations : 0         time: 0.00
Mixed integer           - relaxations: 0         time: 0.00

------------------------------------------------------------
Status: Solved
Optimal value (cvx_optval): -31.24