fsst.cone.lp: Computes the solution to the cone problem

In conroylau/lpinfer: An R Package for Inference in Linear Programs

Computes the solution to the cone problem

Description

This function computes the solution to the cone problem.

Usage

fsst.cone.lp(n, omega.i, beta.n, beta.star, lpmodel, indicator, solver)

Arguments

n	The sample size. This is only required if data is omitted in the input.
omega.i	The matrix \widehat{\bm{\Omega}}^i_n, i.e. the regularized matrix for \widehat{\bm{\Sigma}}^{\beta^\star}_{n,\bar{\rho}}.
beta.n	The sample \widehat{\bm{\beta}}_n vector that is defined as \widehat{\bm{\beta}}_n \equiv (\widehat{\bm{\beta}}_{{\rm obs},n}, \bm{\beta}_{{\rm shp},n}, \bm{\beta}_{{\rm tgt}})'.
beta.star	The starred version of the beta.n vector, i.e. \widehat{\bm{\beta}}^\star_n.
lpmodel	The lpmodel object.
indicator	A binary variable that equals to 1 for d \geq p and equals to 0 for d < p.
solver	The name of the linear and quadratic programming solver that is used to obtain the solution to linear and quadratic programs. The solvers supported by this package are cplexAPI, gurobi, limSolve and Rcplex.

Value

Returns the optimal point and optimal value.

objval	The optimal value.
x	The optimal point.

conroylau/lpinfer documentation built on Oct. 25, 2024, 4 a.m.