TY - GEN
T1 - Moving Least Squares regression for high dimensional simulation metamodeling
AU - Salemi, Peter
AU - Nelson, Barry L.
AU - Staum, Jeremy
PY - 2012
Y1 - 2012
N2 - Interpolation and smoothing methods form the basis of simulation metamodeling. In high dimensional metamodeling problems, larger numbers of design points are needed to build an accurate metamodel. This paper introduces a procedure to implement a smoothing method called Moving Least Squares regression in high dimensional metamodeling problems with a large number of design points. We test the procedure with two queueing examples: a multi-product M/G/1 queue and a multi-product Jackson network.
AB - Interpolation and smoothing methods form the basis of simulation metamodeling. In high dimensional metamodeling problems, larger numbers of design points are needed to build an accurate metamodel. This paper introduces a procedure to implement a smoothing method called Moving Least Squares regression in high dimensional metamodeling problems with a large number of design points. We test the procedure with two queueing examples: a multi-product M/G/1 queue and a multi-product Jackson network.
UR - http://www.scopus.com/inward/record.url?scp=84874723263&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84874723263&partnerID=8YFLogxK
U2 - 10.1109/WSC.2012.6465122
DO - 10.1109/WSC.2012.6465122
M3 - Conference contribution
AN - SCOPUS:84874723263
SN - 9781467347792
T3 - Proceedings - Winter Simulation Conference
BT - Proceedings of the 2012 Winter Simulation Conference, WSC 2012
T2 - 2012 Winter Simulation Conference, WSC 2012
Y2 - 9 December 2012 through 12 December 2012
ER -