Using Randomization to Break the Curse of Dimensionality
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Other versions of this item:
- John Rust, 1997. "Using Randomization to Break the Curse of Dimensionality," Econometrica, Econometric Society, vol. 65(3), pages 487-516, May.
- John Rust & Department of Economics & University of Wisconsin, 1994. "Using Randomization to Break the Curse of Dimensionality," Computational Economics 9403001, University Library of Munich, Germany, revised 19 Nov 1996.
References listed on IDEAS
- Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
- Ariel Pakes & Paul McGuire, 1997. "Stochastic Algorithms for Dynamic Models: Markov Perfect Equilibrium, and the 'Curse' of Dimensionality," Cowles Foundation Discussion Papers 1144, Cowles Foundation for Research in Economics, Yale University.
- Tauchen, George & Hussey, Robert, 1991. "Quadrature-Based Methods for Obtaining Approximate Solutions to Nonlinear Asset Pricing Models," Econometrica, Econometric Society, vol. 59(2), pages 371-396, March.
- Anderson, Evan W. & McGrattan, Ellen R. & Hansen, Lars Peter & Sargent, Thomas J., 1996.
"Mechanics of forming and estimating dynamic linear economies,"
Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.),Handbook of Computational Economics, edition 1, volume 1, chapter 4, pages 171-252,
- Lars Peter Hansen & Ellen R. McGrattan & Thomas J. Sargent, 1994. "Mechanics of forming and estimating dynamic linear economies," Staff Report 182, Federal Reserve Bank of Minneapolis.
- Evan W. Anderson & Lars Peter Hansen & Ellen R. McGrattan & Thomas J. Sargent, 1995. "On the mechanics of forming and estimating dynamic linear economies," Staff Report 198, Federal Reserve Bank of Minneapolis.
- Keane, Michael P & Wolpin, Kenneth I, 1994.
"The Solution and Estimation of Discrete Choice Dynamic Programming Models by Simulation and Interpolation: Monte Carlo Evidence,"
The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 648-672, November.
- Michael P. Keane & Kenneth I. Wolpin, 1994. "The solution and estimation of discrete choice dynamic programming models by simulation and interpolation: Monte Carlo evidence," Staff Report 181, Federal Reserve Bank of Minneapolis.
- Judd, Kenneth L., 1996. "Approximation, perturbation, and projection methods in economic analysis," Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.),Handbook of Computational Economics, edition 1, volume 1, chapter 12, pages 509-585, Elsevier.
- Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1.
More about this item
Keywordseconometrics ; probability;
- C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
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