Bayesian Sparse Estimation Using Double Lomax Priors

<table>Double Lomax prior at zero position, with <svg height="15.35" id="M71" style="vertical-align:-3.56265pt" version="1.1" viewbox="0 0 36.099998 15.35" width="36.099998" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<g transform="matrix(.017,-0,0,-.017,.062,10.862)"><path d="M471 401q0 -32 -14 -91l-83 -376q-30 -146 -21 -180l-7 -15q-22 0 -47.5 23.5t-25.5 40.5q0 49 53 271l53 224q4 18 6.5 31t3.5 22.5t1 15t-2 9t-4.5 4.5t-6.5 1q-31 0 -100.5 -63.5t-126.5 -145.5q-16 -53 -40 -163q-48 -11 -74 -21l-7 8l82 341q9 36 -4 36
q-8 0 -28.5 -14t-38.5 -32l-17 22q41 43 85 71t66 28q23 0 23 -39q0 -19 -10 -64l-24 -103h2q77 101 201 182q37 24 74 24q31 0 31 -47z" id="x1D702"></path></g><g transform="matrix(.017,-0,0,-.017,13.169,10.862)"><path d="M535 323h-483v50h483v-50zM535 138h-483v50h483v-50z" id="x3D"></path></g><g transform="matrix(.017,-0,0,-.017,27.872,10.862)"><path d="M384 0h-275v27q67 5 81.5 18.5t14.5 68.5v385q0 38 -7.5 47.5t-40.5 10.5l-48 2v24q85 15 178 52v-521q0 -55 14.5 -68.5t82.5 -18.5v-27z" id="x31"></path></g>
</svg> for various values of <svg height="16.6625" id="M72" style="vertical-align:-3.56265pt" version="1.1" viewbox="0 0 11.0375 16.6625" width="11.0375" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<g transform="matrix(.017,-0,0,-.017,.062,12.162)"><path d="M619 670q0 -13 -9 -26t-18 -19q-13 -10 -25 2q-36 38 -66 38q-31 0 -54.5 -50t-45.5 -185h120l-20 -31l-107 -12q-23 -138 -57 -293q-27 -122 -55 -184.5t-75 -109.5q-60 -61 -114 -61q-25 0 -47.5 15t-22.5 31q0 17 31 44q11 8 20 -1q10 -11 31 -19t35 -8q26 0 47 19
q34 34 71 253l54 315h-90l-3 12l31 30h70q28 138 90 204q35 37 75 57.5t70 20.5q26 0 45 -14t19 -28z" id="x1D453"></path></g>
</svg>.</table>

Mathematical Problems in Engineering

Bayesian Sparse Estimation Using Double Lomax Priors

Figure 1