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Dear useRs, - I am pleased to announce that the R package OHPL is now available on CRAN (https://CRAN.R-project.org/package=OHPL). The package implements the ordered homogeneity pursuit lasso (OHPL) algorithm for group variable selection proposed in Lin et al. (2017) <doi:10.1016/j.chemolab.2017.07.004>. The OHPL method exploits the homogeneity structure in high-dimensional data and enjoys the grouping effect to select groups of important variables automatically. This feature makes it particularly useful for high-dimensional datasets with strongly correlated variables, such as spec...

...ed Partial Least Squares - is now available on CRAN. It implements the methods described in N. Kr?mer, A.-L. Boulesteix, G. Tutz "Penalized Partial Least Squares with Applications to B-Spline Transformations and Functional Data" Chem. Intell. Lab. Sys. 2008 http://dx.doi.org/10.1016/j.chemolab.2008.06.009 Features of the package include * the estimation of functional data with penalized PLS, * the estimation of generalized additive models with penalized PLS based on spline transformations, * model selection for both methods based on cross validation. The most important changes since...

...ed Partial Least Squares - is now available on CRAN. It implements the methods described in N. Kr?mer, A.-L. Boulesteix, G. Tutz "Penalized Partial Least Squares with Applications to B-Spline Transformations and Functional Data" Chem. Intell. Lab. Sys. 2008 http://dx.doi.org/10.1016/j.chemolab.2008.06.009 Features of the package include * the estimation of functional data with penalized PLS, * the estimation of generalized additive models with penalized PLS based on spline transformations, * model selection for both methods based on cross validation. The most important changes since...

Dear useRs, - I am pleased to announce that the R package OHPL is now available on CRAN (https://CRAN.R-project.org/package=OHPL). The package implements the ordered homogeneity pursuit lasso (OHPL) algorithm for group variable selection proposed in Lin et al. (2017) <doi:10.1016/j.chemolab.2017.07.004>. The OHPL method exploits the homogeneity structure in high-dimensional data and enjoys the grouping effect to select groups of important variables automatically. This feature makes it particularly useful for high-dimensional datasets with strongly correlated variables, such as spec...

> On Aug 14, 2017, at 12:22 PM, fs <mail at friedrich-schuster.de> wrote: > > Hi, and sorry for asking such an unspecific question. > > Does anybody know of statistical / data mining methods that are available in R > that are not in SAS ? With SAS I mean the SAS System Version 9.4 and SAS > Enterprise Miner. I don't expect a complete list, just two or three

Hi, and sorry for asking such an unspecific question. Does anybody know of statistical / data mining methods that are available in R that are not in SAS ? With SAS I mean the SAS System Version 9.4 and SAS Enterprise Miner. I don't expect a complete list, just two or three examples or hints where and what to look for. I found some older comparisons, and the R methods mentioned there