全球智库信息集成服务系统(G2TT): One-node Quadrature Beats Monte Carlo: A Generalized Stochastic Simulation Algorithm

G2TT

来源类型	Working Paper
规范类型	报告
DOI	10.3386/w16708
来源ID	Working Paper 16708
	One-node Quadrature Beats Monte Carlo: A Generalized Stochastic Simulation Algorithm
	Kenneth Judd; Lilia Maliar; Serguei Maliar
发表日期	2011-01-18
出版年	2011
语种	英语
摘要	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.
主题	Microeconomics ; Mathematical Tools
URL	https://www.nber.org/papers/w16708
来源智库	National Bureau of Economic Research (United States)
引用统计
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/574383
推荐引用方式 GB/T 7714	Kenneth Judd,Lilia Maliar,Serguei Maliar. One-node Quadrature Beats Monte Carlo: A Generalized Stochastic Simulation Algorithm. 2011.