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Designing algorithms and bootstrap programme in R

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 01 Jan 2015Publisher:AIP Publishing LLCJournal:AIP Conference Proceedings, volume 1,692, page 20,023 (issn: 0094-243X, Copyright policy )
Authors: Vera Maya Santi;

doi: 10.1063/1.4936451

Designing algorithms and bootstrap programme in R

Abstract

Resampling methods offer strategies to estimate the sampling distribution of a statistic. In this article, the problem involving the use of Bootstrap Method for estimating linear regression parameters have been indentified. We developed resampling Bootstrap algorithms for estimation of linear regression parameters. Computer programs were written in R for the implementation of these algorithms to estimate linear regression parameters.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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