Please use this identifier to cite or link to this item:
http://dspace.mediu.edu.my:8181/xmlui/handle/10261/1766Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.creator | Creel, Michael | - |
| dc.date | 2007-10-31T12:23:23Z | - |
| dc.date | 2007-10-31T12:23:23Z | - |
| dc.date | 2005-01-10 | - |
| dc.date.accessioned | 2017-01-31T00:57:50Z | - |
| dc.date.available | 2017-01-31T00:57:50Z | - |
| dc.identifier | http://hdl.handle.net/10261/1766 | - |
| dc.identifier.uri | http://dspace.mediu.edu.my:8181/xmlui/handle/10261/1766 | - |
| dc.description | This paper shows how a high level matrix programming language may be used to perform Monte Carlo simulation, bootstrapping, estimation by maximum likelihood and GMM, and kernel regression in parallel on symmetric multiprocessor computers or clusters of workstations. The implementation of parallelization is done in a way such that an investigator may use the programs without any knowledge of parallel programming. A bootable CD that allows rapid creation of a cluster for parallel computing is introduced. Examples show that parallelization can lead to important reductions in computational time. Detailed discussion of how the Monte Carlo problem was parallelized is included as an example for learning to write parallel programs for Octave. | - |
| dc.language | eng | - |
| dc.relation | UFAE and IAE Working Papers | - |
| dc.relation | 637.05 | - |
| dc.rights | openAccess | - |
| dc.subject | Parallel computing | - |
| dc.subject | Kernel regression | - |
| dc.subject | Monte Carlo | - |
| dc.subject | Bootstrapping | - |
| dc.subject | Maximum likelihood | - |
| dc.subject | GMM | - |
| dc.title | User-Friendly Parallel Computations with Econometric Examples | - |
| dc.type | Documento de trabajo | - |
| Appears in Collections: | Digital Csic | |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.