Abstract : In this paper we determine the proximity functions of the sum and the maximum of componentwise (reciprocal) quotients of positive vectors. For the sum of quotients, denoted by $Q_1$, the proximity function is just a componentwise shrinkage function which we call q-shrinkage. This is similar to the proximity function of the ℓ1-norm which is given by componentwise soft shrinkage. For the maximum of quotients $Q_∞$, the proximal function can be computed by first order primal dual methods involving epigraphical projections. The proximity functions of $Q_ν$ , $ν = 1,∞$ are applied to solve convex problems of the form $argmin_x Q _ν ( Ax/b )$ subject to $x ≥ 0$, $1^\top x ≤ 1$. Such problems are of interest in selectivity estimation for cost-based query optimizers in database management systems.