TY - GEN
T1 - Low bias integrated path estimators
AU - Calvin, James M.
PY - 2007
Y1 - 2007
N2 - We consider the problem of estimating the time-average variance constant for a stationary process. A previous paper described an approach based on multiple integrations of the simulation output path, and described the efficiency improvement that can result compared with the method of batch means (which is a special case of the method). In this paper we describe versions of the method that have low bias for moderate simulation run lengths. The method constructs an estimator based on applying a quadratic function to the simulation output. The particular quadratic form is chosen to minimize variance subject to constraints on the order of the bias. Estimators that are first-order and second-order unbiased are described.
AB - We consider the problem of estimating the time-average variance constant for a stationary process. A previous paper described an approach based on multiple integrations of the simulation output path, and described the efficiency improvement that can result compared with the method of batch means (which is a special case of the method). In this paper we describe versions of the method that have low bias for moderate simulation run lengths. The method constructs an estimator based on applying a quadratic function to the simulation output. The particular quadratic form is chosen to minimize variance subject to constraints on the order of the bias. Estimators that are first-order and second-order unbiased are described.
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U2 - 10.1109/WSC.2007.4419616
DO - 10.1109/WSC.2007.4419616
M3 - Conference contribution
AN - SCOPUS:49749084358
SN - 1424413060
SN - 9781424413065
T3 - Proceedings - Winter Simulation Conference
SP - 303
EP - 307
BT - Proceedings of the 2007 Winter Simulation Conference, WSC
T2 - 2007 Winter Simulation Conference, WSC
Y2 - 9 December 2007 through 12 December 2007
ER -