[R-pkgs] randomSurvivalForest 3.0.0 now available

[Udaya B. Kogalur]

Dear useRs:

Release 3.0.0 of the randomSurvivalForest, an ensemble tree method for
the analysis of right censored survival data,  package is now
available.

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CHANGES TO RELEASE 3.0.0

Release 3.0.0 represents a major upgrade in the functionality of the
2.x releases.  Key changes are as follows:

o Missing data can be imputed in both grow and predict mode.  This
  applies to variables as well as time and censoring outcome values.
  Values are imputed dynamically as the tree is grown using a new tree
  imputation methodology.  This produces an imputed forest which can be
  used for prediction purposes on test data sets with missing data.

o Importance values for variables are returned in predict mode when test
  data contains outcomes as well as variables.

o Fixed some bugs in plot.variable().  Thanks to Andy J. Minn for
pointing this out.

o Minor modification of PMML representation of RSF forest output to accomodate
  imputation.  The method of random seed chain recovery has been altered.
  Note that forests produced with prior releases will have to be
  regenerated using this release.  We apologize for the inconvenience.

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Thanks.

ubk

ubk2101 at columbia.edu

Udaya B. Kogalur, Ph.D.
Kogalur Shear Corporation
5425 Nestleway Drive, Suite L1
Clemmons, NC 27012