أعرض تسجيلة المادة بشكل مبسط

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


الملفات في هذه المادة

الملفات الحجم الصيغة عرض

لا توجد أي ملفات مرتبطة بهذه المادة.

هذه المادة تبدو في المجموعات التالية:

أعرض تسجيلة المادة بشكل مبسط