[R-pkgs] randomForestSRC 1.0.0 is now available on CRAN

[Udaya B. Kogalur]

Dear userRs:

Please find randomForestSRC 1.0.0 now available for download on CRAN.

Random Forests for Survival, Regression, and Classification provides a
unified treatment of Breiman's random forests (Breiman 2001) for
survival, regression, and classification problems.  The underlying
code is based on Ishwaran and Kogalur's now retired
"randomSurvivalForest" package and has been significantly refactored
for improved computational speed.  It implements Breiman's random
forests for a variety of data settings.  Numeric or categorical
(factor) responses yield regression and classification forests.
Survival and competing risk forests are grown when the response is
right-censored.  Different splitting rules invoked under deterministic
or random splitting are available for all families.  Variable
predictiveness can be assessed using variable importance (VIMP)
measures for single, as well as grouped variables.  Variable selection
is implemented using minimal depth variable selection. Missing data
(for x-variables and y-outcomes) can be imputed on both training and
test data.

This package implements OpenMP shared-memory parallel programming.
However, the default installation will only execute serially.  To
utilize OpenMP, the target system must first support it.  To install
the package with OpenMP compiler options turned on: (1) Download the
source code for the package.  (2) From the root directory of the
package source run the command "autoconf".  (3) Use "R CMD INSTALL" on
the modified package directory.

Thank you.

ubk

Udaya B. Kogalur, Ph.D.
Adjunct Staff, Dept of Quantitative Health Sciences, Cleveland Clinic Foundation
Consultant, Kogalur Shear Corporation

kogalurshear at gmail.com
Website:  www.kogalur-shear.com