Effectiveness of optimum stratified sampling and estimation in Monte Carlo production simulation

摘要

The paper describes a computer algorithm designed for Monte Carlo production cost. The design seeks to enhance the precision of production cost estimation at a reduced computation time of the existing approach. The techniques included are optimum stratified sampling and ratio estimate. The optimum stratification rule aims to remove any judgmental input and to render the stratification process entirely mechanistic. The estimator, provided by ratio statistics of the sample, can avoid identification of the regression model and thus save computation time. Hence, the effectiveness on precision improvement is demonstrated in this paper.