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Changelog

Source: NEWS.md

quadrupen 0.3-0 (2013-11)

  • major updates
    • added structured ridge regression (regression penalized by structured l2 norm)
    • added corresponding functionality for cross-validation and stability path
  • Minor:
    • removed the not very useful ‘reverse’ argument for plotting
    • added demo for lasso, ridge and use of the criteria function

quadrupen 0.2-4 (2014-01-16)

CRAN release: 2014-01-16

Minor:
+   memory leak corrected (sp_mat declaration)
+   linking to Rcpp/RcppArmadillo headers (requires R 3.0-2)

quadrupen 0.2-4 (2013-11-01)

CRAN release: 2014-01-16

  • added a ‘lasso’ function, simple wrapper to the elastic-net ‘function’
  • added computation of degrees of freedom (for elastic net and bounded regression)
  • added a method to compute penalized criteria (BIC/AIC) of a quadrupen fit, with plot

quadrupen 0.2-2 (2013-04-08)

CRAN release: 2013-04-08

  • minor fix to comply with recent ggplot2 updates.

quadrupen 0.2-1 (2013-02-27)

CRAN release: 2013-02-27

  • minor fix to pass CRAN check on Windows operating systems.

quadrupen 0.2-0 (2013-02-26)

  • Major updates
    • added bounded regression (regression penalized by infinity norm + structered l2 norm)
    • added corresponding functionalies for cross-validation and stability path
  • Minor updates
  • corrected wrong annotations of the stability path (PFER)
  • handled normalization internally (‘normalize’ is no longer a parameter)
  • more simple internal handling of penscales and correction of the rescaling of the intercept
  • better use of multicore features
  • handled runtime error exception in RcppArmadillo when the system is singular (end of the solution path) A consequence is quadrupen is less likely to crash due to user’s “bad” parametrization
  • simplification of the C++ code, bugs corrected, probably new ones added :-’(
  • added ‘examples’ and ‘tests’ directories

quadrupen 0.1-0 (2012-10-09)

CRAN release: 2012-10-10

  • first build: structured elastic-net with (weighted) quadratic loss, cross-validation and stability selection methods.