LargeRegression 1.0

Large Regressions

Released Aug 6, 2011 by

This package is available for Renjin and there are no known compatibility issues.


Matrix 1.2-14

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



This package can be included as a dependency from a Java or Scala project by including the following your project's pom.xml file. Read more about embedding Renjin in JVM-based projects.

    <name>bedatadriven public repo</name>

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Renjin CLI

If you're using Renjin from the command line, you load this library by invoking:


Test Results

This package was last tested against Renjin 0.9.2644 on Jun 2, 2018.



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