Performance Evaluation of Statistical Functions

dc.contributor.author	André Valente Rodrigues	en
dc.contributor.author	Carla Pereira Silva	en
dc.contributor.author	Borges,PVK	en
dc.contributor.author	Silva,S	en
dc.contributor.author	Inês Dutra	en
dc.date.accessioned	2018-01-18T15:18:40Z
dc.date.available	2018-01-18T15:18:40Z
dc.date.issued	2015	en
dc.description.abstract	Statistical data analysis methods are well known for their difficulty in handling large number of instances or large number of parameters. This is most noticeable in the presence of "big data", i.e., of data that are heterogeneous, and come from several sources, which makes their volume increase very rapidly. In this paper, we study popular and well-known statistical functions generally applied to data analysis, and assess their performance using our own implementation (DataIP) 1, MatLab and R. We show that DataIP outperforms MatLab and R by several orders of magnitude and that the design and implementation of these functions need to be rethought to adapt to today's data challenges. © 2015 IEEE.	en
dc.identifier.uri	http://repositorio.inesctec.pt/handle/123456789/6977
dc.identifier.uri	http://dx.doi.org/10.1109/SmartCity.2015.159	en
dc.language	eng	en
dc.relation	6210	en
dc.relation	5139	en
dc.relation	6197	en
dc.rights	info:eu-repo/semantics/openAccess	en
dc.title	Performance Evaluation of Statistical Functions	en
dc.type	conferenceObject	en
dc.type	Publication	en

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