An edition of A cluster-grid projection method (2010)

A cluster-grid projection method

solving problems with high dimensionality

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A cluster-grid projection method
Kenneth L. Judd, Kenneth L. Ju ...
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Last edited by MARC Bot
September 25, 2020 | History
An edition of A cluster-grid projection method (2010)

A cluster-grid projection method

solving problems with high dimensionality

  • 0 Want to read
  • 0 Currently reading
  • 0 Have read

"We develop a projection method that can solve dynamic economic models with a large number of state variables. A distinctive feature of our method is that it operates on the ergodic set realized in equilibrium: we simulate a model, distinguish clusters on simulated series and use the clusters' centers as a grid for projections. Making the grid endogenous to the model allows us to avoid costs associated with finding a solution in areas of state space that are never visited in equilibrium. On a standard desktop computer, we calculate linear and quadratic solutions to a multi-country growth model with up to 400 and 80 state variables, respectively. Our solutions are global, and their accuracy does not rapidly decline away from steady state"--National Bureau of Economic Research web site.

Publish Date
Language
English

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Edition Availability
Cover of: A cluster-grid projection method
A cluster-grid projection method: solving problems with high dimensionality
2010, National Bureau of Economic Research
electronic resource : in English

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Book Details


Edition Notes

Title from PDF file as viewed on 5/11/2010.

Includes bibliographical references.

Also available in print.

System requirements: Adobe Acrobat Reader.

Mode of access: World Wide Web.

Published in
Cambridge, MA
Series
NBER working paper series -- working paper 15965, Working paper series (National Bureau of Economic Research : Online) -- working paper no. 15965.

Classifications

Library of Congress
HB1

The Physical Object

Format
[electronic resource] :

ID Numbers

Open Library
OL30508397M
LCCN
2010656005

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September 25, 2020 Created by MARC Bot Imported from Library of Congress MARC record