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This package was removed from CRAN on 2014-11-24. Its history is shown below.
Reason: maintainer address <<jeff.ct.wong@stanford.edu> bounced
Details below reflect version 1.0, its last release before removal.

LargeRegression

1.0

Large Regressions

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Overview

About
1 releasesCRAN page ↗

Uses gradient descent to minimize the sum of squared residuals for the regression problem. Can include an L2 penalty on the coefficient matrix. This function is very useful when there is an initial guess of what B should be in Y = XB. In general, this function performs faster than R's lm function. GPU acceleration can be used to make this function extremely fast. This package suggests cudaMatrixOps, which is not on CRAN but can be downloaded at stanford.edu/~jeffwong.

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Code health
Yes
Tests · ratio 1.43
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Coverage
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Dependencies · direct

Documentation

Documentation
READMENoVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo
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References docs
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Downloads

LargeRegression
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Dependencies

Declared dependencies
1 external dependency (excludes base and recommended)
Depends (1)
Matrix
Imports (0)
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LinkingTo (0)
none
Suggests (1)
Enhances (0)
none
Reverse dependencies
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Code & Tests

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Package Timeline

1 release. R releases are shown for context.

  • R
    R 3.2.0 released · 2015-04-16
  • archivedRemoved from CRAN
    2014-11-24
    maintainer address <<jeff.ct.wong@stanford.edu> bounced
  • R
    R 3.1.0 released · 2014-04-10
  • R
    R 3.0.0 released · 2013-04-03
  • R
    R 2.15.0 released · 2012-03-30
  • R
    R 2.14.0 released · 2011-10-31
  • 1.0
    2011-08-05
  • R
    R 2.13.0 released · 2011-04-13

Package metadata

Total releases
1
License
GPL
Download size
not tracked yet
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