Case Study: Efficient and Robust Optimal Design for Quantile Regression Based on Linear Programming

CASE STUDY: Efficient and Robust Optimal Design for Quantile Regression Based on Linear Programming

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Instructions for optimization with PSG Run-File, PSG MATLAB Toolbox, PSG MATLAB Subroutines and PSG R.

PROBLEM 1: problem_minimize_variance_of_quantile_error_bound
minimize
linearize = 1
linear(matrix_objcoef)
Constraint: == 0
linearmulti (matrix_lhs)
Box: >= 0
Solver: car
  # of Variables Objective Value Solving Time, PC 2GHz (sec)
Dataset 5,000 0.234215098995E+01 0.05
Environments
R R code Data Solution

PROBLEM 2: problem_minimize_CVaR_of_quantile_error_bound
minimize
linearize = 1
linear(matrix_objcoef)
Constraint: == 0
linearmulti (matrix_lhs)
Box: >= 0
Solver: car
  # of Variables Objective Value Solving Time, PC 2GHz (sec)
Dataset 5,000 0.301224209124E+02 0.05
Environments
R R code Data Solution