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.
--------------------------------------------------------------------------------- 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. --------------------------------------------------------------------------------- Thanks. ubk [EMAIL PROTECTED] Udaya B. Kogalur, Ph.D. Kogalur Shear Corporation 5425 Nestleway Drive, Suite L1 Clemmons, NC 27012 _______________________________________________ R-packages mailing list [EMAIL PROTECTED] https://stat.ethz.ch/mailman/listinfo/r-packages ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
