Why Unified Statistics Theory by MCMC Towards Linear and Nonlinear Programming Problems?

Abstract

Unified statistics theory by MCMC is considered. A new proposed algorithm is presented  to obtain surely empirical analysis conclusions in order to turn to surely theoretical analysis results about the behavior of any general linear or nonlinear programming problem in order to introduce a complete framework and to solve any too large dimensional deterministic and probabilistic (the grouping data, both continuous and discrete)  linear or nonlinear programming problems by the proposed algorithm that has two obvious criteria towards the second resounding success of unified statistics theory by MCMC.