similar to: randomSurvivalForest 2.1.0 now available

Dear useRs: Release 2.0.0 of the randomSurvivalForest package is now available. --------------------------------------------------------------------------------- CHANGES TO RELEASE 2.0.0 Release 2.0.0 represents a major upgrade in the functionality and stability of the original 1.0.0 release. Key changes are as follows: o Two new splitting rules, 'logrankscore' and

Dear useRs: Release 2.0.0 of the randomSurvivalForest package is now available. --------------------------------------------------------------------------------- CHANGES TO RELEASE 2.0.0 Release 2.0.0 represents a major upgrade in the functionality and stability of the original 1.0.0 release. Key changes are as follows: o Two new splitting rules, 'logrankscore' and

Dear useRs: Release 3.2.0 of the CRAN package randomSurvivalForest is now available. ---------------------------------------------------------------------------------------------- Release 3.2.0 represents a significant upgrade in the functionality of the product. Key changes are as follows: o A second method of perturbing the data set in order to calculate variable importance (VIMP) has been

Dear useRs: Release 3.2.0 of the CRAN package randomSurvivalForest is now available. ---------------------------------------------------------------------------------------------- Release 3.2.0 represents a significant upgrade in the functionality of the product. Key changes are as follows: o A second method of perturbing the data set in order to calculate variable importance (VIMP) has been

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

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

Please find release 3.6.0 of the package "randomSurvivalForest" now available for download on CRAN. --------------------------------------------------------------------------------- CHANGES TO RELEASE ?3.6.0 RELEASE 3.6.0 represents the last and final major upgrade of this product. ?Current and future functionality will migrate to the new CRAN package, Random Forests for Survival,

Please find release 3.6.0 of the package "randomSurvivalForest" now available for download on CRAN. --------------------------------------------------------------------------------- CHANGES TO RELEASE ?3.6.0 RELEASE 3.6.0 represents the last and final major upgrade of this product. ?Current and future functionality will migrate to the new CRAN package, Random Forests for Survival,

Please find release 3.5.0 of the CRAN package "randomSurvivalForest" now posted on CRAN. Thank you. ubk2101 at columbia.edu Udaya B. Kogalur, Ph.D. Kogalur Shear Corporation 5425 Nestleway Drive, Suite L1 Clemmons, NC 27012 --------------------------------------------------------------------------------- CHANGES TO RELEASE 3.5.0 RELEASE 3.5.0 represents a significant upgrade in the

Please find release 3.5.0 of the CRAN package "randomSurvivalForest" now posted on CRAN. Thank you. ubk2101 at columbia.edu Udaya B. Kogalur, Ph.D. Kogalur Shear Corporation 5425 Nestleway Drive, Suite L1 Clemmons, NC 27012 --------------------------------------------------------------------------------- CHANGES TO RELEASE 3.5.0 RELEASE 3.5.0 represents a significant upgrade in the

Apologies for any obtuseness in the following. We have been working on Version 2.0 of the randomSurvivalForest CRAN package and we're encountering a perplexing 'memory not mapped' segfault that we believe is "influenced" by GC. We essentially have two R functions, rsf.default(..), and predict.rsf(..) and two corresponding entry points, rsfGrow(...), and rsfPredict(...),

Hi, I am having some trouble using R 2.13.1 for generating a pmml object of of class "c('randomForest.formula', 'randomForest')" I see that these methods are available: > methods(pmml) [1] pmml.coxph* pmml.hclust* pmml.itemsets* pmml.kmeans* pmml.ksvm* pmml.lm* pmml.multinom* pmml.nnet* pmml.rpart* [10] pmml.rsf* pmml.rules* pmml.survreg*

Please find release 1.0.0 of the new CRAN package "spikeslab" now available for download. Thank you. --------------------------------------------------------------------------------- RELEASE 1.0.0 is the first and initial release of this package. Fits a rescaled spike and slab model using a continuous bimodal prior. Can be used for prediction and variable selection in low and

Please find release 1.0.0 of the new CRAN package "spikeslab" now available for download. Thank you. --------------------------------------------------------------------------------- RELEASE 1.0.0 is the first and initial release of this package. Fits a rescaled spike and slab model using a continuous bimodal prior. Can be used for prediction and variable selection in low and

Please find release 1.1.0 of the CRAN package "spikeslab" now available for download. Spike and slab for prediction and variable selection in linear regression models. Uses a generalized elastic net for variable selection. CHANGES TO RELEASE 1.1.0 RELEASE 1.1.0 is a recommended upgrade of the product. o cv.spikeslab() now takes advantage of the CRAN package "snow". It

Please find release 1.1.0 of the CRAN package "spikeslab" now available for download. Spike and slab for prediction and variable selection in linear regression models. Uses a generalized elastic net for variable selection. CHANGES TO RELEASE 1.1.0 RELEASE 1.1.0 is a recommended upgrade of the product. o cv.spikeslab() now takes advantage of the CRAN package "snow". It

We recently posted randomForestSRC on CRAN. It uses OpenMP in the native code extensively. We set the default number of cores to two (2), but we typically run it at the maximum (omp_get_max_threads()) during analysis. Currently, users need to set options(), set an environment variable, or edit their .Rprofile to use more than two cores. We followed the protocol for mc.cores in mclapply() in

Dear useRs, Release 1.0.0 of the new R package 'randomSurvivalForest' is now available on CRAN and its mirrors. The package implements Ishwaran and Kogalur's Random Survival Forests algorithm for right censored survival data. The algorithm is closely patterned after Breiman's random forests, but suitably modified for the survival setting. Some key features are: o An ensemble

I'm using randomSurvivalForest to predict survival from a rather small sample. As it's not enough data to have training and validation set, I rely on the "Estimate of error rate" computed by the randomForest. If I understand the method correctly, it repeatedly partitions the data into varying training/validation sets during the learning steps, which also produces the

Dear useRs: It's been some time since we last sent out an announcement, so this one will cover more than just the last update. The latest release of randomForestSRC is now available on CRAN at: https://CRAN.R-project.org/package=randomForestSRC The GitHub repository, through which we prefer to receive bug reports, is at: https://github.com/kogalur/randomForestSRC If you do find issues,