One-node quadrature beats monte carlo
Subtitle: a generalized stochastic simulation algorithm
By: Kenneth Judd, Lilia Maliar, Serguei Maliar
Contributors: Maliar, Lilia; Maliar, Serguei; National Bureau of Economic Research
Series: NBER working paper series -- working paper 16708; Working paper series (National Bureau of Economic Research : Online) -- working paper no. 16708.
Publisher: National Bureau of Economic Research
Published: 2011
Place of publication: Cambridge, MA
Language: eng
Format: Electronic resource
Description: "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.
Notes: Title from PDF file as viewed on 4/21/2011.

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