eShuffle specifications

Information


Unique identifier OMICS_16107
Name eShuffle
Software type Framework/Library
Interface Command line interface
Restrictions to use Academic or non-commercial use
Operating system Unix/Linux
Computer skills Advanced
Stability Stable
Maintained Yes

Versioning


No version available

Maintainer


  • person_outline Costas Maranas

Additional information


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Publication for eShuffle

eShuffle citation

library_books

Simultaneous Analysis and Quality Assurance for Diffusion Tensor Imaging

2013
PLoS One
PMCID: 3640065
PMID: 23637895
DOI: 10.1371/journal.pone.0061737

[…] pproach through the method used herein. For a fixed spatial location the errors are, εj = |Sm,j – Sf,j |. For each Monte-Carlo simulation, the J errors are shuffled and given a random sign (+ or -), ±εshuffle. The use of the random sign is what makes this a ‘wild’ bootstrap method. Wild-bootstrap data, Sbs,, is synthesized by adding the shuffled errors to the fitted data: Sbs = Sf +( ±εshuffle ).T […]

eShuffle institution(s)
Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA; Department of Chemistry, The Pennsylvania State University, University Park, PA, USA
eShuffle funding source(s)
This work was supported by the Life Science Consortium at Penn State and National Science Foundation Career Award CTS-9701771.

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