TY - GEN
T1 - A reflection-based variance reduction technique for sum of random variables
AU - Liu, Guangwu
PY - 2011
Y1 - 2011
N2 - Monte Carlo simulation has been widely used as a standard tool for estimating expectations. In this paper we develop a variance reduction technique for a particular case when the expectation is taken under a constraint that a sum of random variables is larger than a threshold. The proposed technique is based on a reflection argument on the sample space and requires knowing the joint density of the random variables. It turns out the technique can always guarantee a variance reduction. More importantly, the technique sheds light on how observations violating the constraint can be used more efficiently in estimation, compared to crude Monte Carlo. © 2011 IEEE.
AB - Monte Carlo simulation has been widely used as a standard tool for estimating expectations. In this paper we develop a variance reduction technique for a particular case when the expectation is taken under a constraint that a sum of random variables is larger than a threshold. The proposed technique is based on a reflection argument on the sample space and requires knowing the joint density of the random variables. It turns out the technique can always guarantee a variance reduction. More importantly, the technique sheds light on how observations violating the constraint can be used more efficiently in estimation, compared to crude Monte Carlo. © 2011 IEEE.
UR - https://www.scopus.com/pages/publications/84863277869
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84863277869&origin=recordpage
U2 - 10.1109/WSC.2011.6148071
DO - 10.1109/WSC.2011.6148071
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781457721083
SP - 3790
EP - 3799
BT - Proceedings - Winter Simulation Conference
T2 - 2011 Winter Simulation Conference, WSC 2011
Y2 - 11 December 2011 through 14 December 2011
ER -