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Numerical analysis / Data analysis / Multivariate statistics / Cluster analysis / Numerical integration / Ergodic theory / K-means clustering / Monte Carlo method / Gauss–Hermite quadrature / Statistics / Applied mathematics / Probability and statistics


NBER WORKING PAPER SERIES A CLUSTER-GRID PROJECTION METHOD: SOLVING PROBLEMS WITH HIGH DIMENSIONALITY Kenneth L. Judd Lilia Maliar
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Document Date: 2010-08-27 18:08:38

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Santos / Cambridge / /

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Facility

Stanford University / Economics University of Alicante Campus San Vicente del Raspeig Ap / /

IndustryTerm

linear and quadratic solutions / hierarchical algorithm / highdimensional applications / time series solution / approach using clustering algorithms / technology levels / parameterized expectations algorithm / closed-form solution / su ciently accurate solutions / dimensional applications / technology shock / numerical solution / /

MarketIndex

set 10 / /

Organization

Hoover Institution / Stanford University / NATIONAL BUREAU OF ECONOMIC RESEARCH / Economics University / Kenneth L. Judd Hoover Institution / Stanford University Stanford / /

Person

Lilia Maliar / Kenneth L. Judd / Gaspar / Serguei Maliar / /

Position

Fisher / representative / /

ProvinceOrState

Massachusetts / /

SportsLeague

Stanford University / /

Technology

parameterized expectations algorithm / 2.1 Hierarchical algorithm / clustering algorithms / K-means algorithms / simulation / 3.2 Clustering algorithms / /

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http /

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