Rcpp reaches 100 dependents on CRAN

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With the arrival earlier today of the stochvol package onto the CRAN network for R, our Rcpp project reached a new milestone: 100 packages have either a Depends:, Imports: or LinkingTo: statement on it.

The full list will always be at the bottom of the CRAN page for Rcpp; I also manually edit a list on my Rcpp page. But for the record as of today, here is the current list as produced by a little helper script I keep:

 acer                apcluster           auteur             
 bcp                 bfa                 bfp                
 bifactorial         blockcluster        ccaPP              
 cda                 classify            clusteval          
 ConConPiWiFun       EpiContactTrace     fastGHQuad         
 fdaMixed            forecast            fugeR              
 GeneticTools        gMWT                gof                
 gRbase              gRim                growcurves         
 GUTS                jaatha              KernSmoothIRT      
 LaF                 maxent              mets               
 minqa               mirt                mRMRe              
 multmod             mvabund             MVB                
 NetworkAnalysis     ngspatial           oem                
 openair             orQA                parser             
 pbdBASE             pbdDMAT             phom               
 phylobase           planar              psgp               
 quadrupen           Rchemcpp            Rclusterpp         
 RcppArmadillo       RcppBDT             rcppbugs           
 RcppClassic         RcppClassicExamples RcppCNPy           
 RcppDE              RcppEigen           RcppExamples       
 RcppGSL             RcppOctave          RcppRoll           
 RcppSMC             RcppXts             rforensicbatwing   
 rgam                RInside             Rmalschains        
 Rmixmod             robustgam           robustHD           
 rococo              RProtoBuf           RQuantLib          
 RSNNS               RSofia              rugarch            
 RVowpalWabbit       SBSA                sdcMicro           
 sdcTable            simFrame            spacodiR           
 sparseHessianFD     sparseLTSEigen      SpatialTools       
 stochvol            surveillance        survSNP            
 termstrc            tmg                 transmission       
 trustOptim          unmarked            VIM                
 waffect             WideLM              wordcloud          

And not to be forgotten is BioConductor which has another 10:

 ddgraph            GeneNetworkBuilder GOSemSim          
 GRENITS            mosaics            mzR               
 pcaMethods         Rdisop             Risa              

As developers of Rcpp, we are both proud and also a little humbled. The packages using Rcpp span everything from bringing new libraries to R, to implementing faster ways of doing things we have before to doing completely new things. It is an exciting time to be using R, and to be connecting R to C++, especially with so many exciting things happening in C++ right now. Follow the Rcpp links for more, and come join us on the Rcpp-devel mailing list to discuss and learn.

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