MARC Record from Library of Congress

LEADER: 01958nam a22003017a 4500
001 2011655936
003 DLC
005 20110421150714.0
007 cr |||||||||||
008 110421s2011 mau sb 000 0 eng
010 $a 2011655936
040 $aDLC$cDLC
050 00 $aHB1
100 1 $aJudd, Kenneth L.
245 10 $aOne-node quadrature beats monte carlo$h[electronic resource] :$ba generalized stochastic simulation algorithm /$cKenneth Judd, Lilia Maliar, Serguei Maliar.
260 $aCambridge, MA :$bNational Bureau of Economic Research,$cc2011.
490 1 $aNBER working paper series ;$vworking paper 16708
538 $aSystem requirements: Adobe Acrobat Reader.
538 $aMode of access: World Wide Web.
500 $aTitle from PDF file as viewed on 4/21/2011.
530 $aAlso available in print.
504 $aIncludes bibliographical references.
520 3 $a"In conventional stochastic simulation algorithms, Monte Carlo integration and curve fitting are merged together and implemented by means of regression. We perform a decomposition of the solution error and show that regression does a good job in curve fitting but a poor job in integration, which leads to low accuracy of solutions. We propose a generalized notion of stochastic simulation approach in which integration and curve fitting are separated. We specifically allow for the use of deterministic (quadrature and monomial) integration methods which are more accurate than the conventional Monte Carlo method. We achieve accuracy of solutions that is orders of magnitude higher than that of the conventional stochastic simulation algorithms"--National Bureau of Economic Research web site.
700 1 $aMaliar, Lilia.
700 1 $aMaliar, Serguei.
710 2 $aNational Bureau of Economic Research.
830 0 $aWorking paper series (National Bureau of Economic Research : Online) ;$vworking paper no. 16708.
856 40 $uhttp://www.nber.org/papers/w16708