a b/partyMod/tests/Predict-regtest.Rout.save 

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R Under development (unstable) (2014-06-29 r66051) -- "Unsuffered Consequences"





  
  

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Copyright (C) 2014 The R Foundation for Statistical Computing





  
  

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Platform: x86_64-unknown-linux-gnu (64-bit)





  
  

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R is free software and comes with ABSOLUTELY NO WARRANTY.





  
  

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You are welcome to redistribute it under certain conditions.





  
  

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Type 'license()' or 'licence()' for distribution details.





  
  

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R is a collaborative project with many contributors.





  
  

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Type 'contributors()' for more information and





  
  

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'citation()' on how to cite R or R packages in publications.





  
  

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Type 'demo()' for some demos, 'help()' for on-line help, or





  
  

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'help.start()' for an HTML browser interface to help.





  
  

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Type 'q()' to quit R.





  
  

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> 





  
  

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> set.seed(290875)





  
  

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> library("party")





  
  

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Loading required package: grid





  
  

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Loading required package: zoo





  
  

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Attaching package: 'zoo'





  
  

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The following objects are masked from 'package:base':





  
  

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    as.Date, as.Date.numeric





  
  

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Loading required package: sandwich





  
  

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Loading required package: strucchange





  
  

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Loading required package: modeltools





  
  

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Loading required package: stats4





  
  

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> if (!require("TH.data"))





  
  

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+     stop("cannot load package TH.data")





  
  

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Loading required package: TH.data





  
  

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> if (!require("coin"))





  
  

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+     stop("cannot load package coin")





  
  

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Loading required package: coin





  
  

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Loading required package: survival





  
  

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Loading required package: splines





  
  

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> 





  
  

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> ### get rid of the NAMESPACE





  
  

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> attach(asNamespace("party"))





  
  

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The following objects are masked from package:party:





  
  

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    cforest, cforest_classical, cforest_control, cforest_unbiased,





  
  

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    conditionalTree, ctree, ctree_control, ctree_memory, edge_simple,





  
  

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    mob, mob_control, node_barplot, node_bivplot, node_boxplot,





  
  

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    node_density, node_hist, node_inner, node_scatterplot, node_surv,





  
  

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    node_terminal, proximity, ptrafo, reweight, sctest.mob, varimp,





  
  

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    varimpAUC





  
  

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> 





  
  

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> data(treepipit, package = "coin")





  
  

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> ct <- ctree(counts ~ ., data = treepipit)





  
  

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> stopifnot(isequal(predict(ct), predict(ct, newdata = treepipit)))





  
  

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> 





  
  

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> 





  
  

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> data(GlaucomaM, package = "TH.data")





  
  

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> ct <- ctree(Class ~ ., data = GlaucomaM)





  
  

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> stopifnot(isequal(predict(ct), predict(ct, newdata = GlaucomaM)))





  
  

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> stopifnot(isequal(predict(ct, type = "prob"), predict(ct, type = "prob", 





  
  

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+                   newdata = GlaucomaM)))





  
  

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> stopifnot(isequal(predict(ct, type = "node"), predict(ct, type = "node", 





  
  

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+                   newdata = GlaucomaM)))





  
  

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> stopifnot(isequal(predict(ct, type = "prob"), treeresponse(ct)))





  
  

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> 





  
  

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> data("GBSG2", package = "TH.data")  





  
  

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> 





  
  

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> GBSG2tree <- ctree(Surv(time, cens) ~ ., data = GBSG2)





  
  

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> stopifnot(isequal(GBSG2tree@predict_response(), 





  
  

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+           GBSG2tree@predict_response(newdata = GBSG2)))





  
  

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> stopifnot(isequal(GBSG2tree@cond_distr_response(), 





  
  

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+           GBSG2tree@cond_distr_response(newdata = GBSG2)))





  
  

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> 





  
  

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> data("mammoexp", package = "TH.data")





  
  

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> attr(mammoexp$ME, "scores") <- 1:3   





  
  

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> attr(mammoexp$SYMPT, "scores") <- 1:4





  
  

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> attr(mammoexp$DECT, "scores") <- 1:3 





  
  

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> names(mammoexp)[names(mammoexp) == "SYMPT"] <- "symptoms"





  
  

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> names(mammoexp)[names(mammoexp) == "PB"] <- "benefit"





  
  

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> 





  
  

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> names(mammoexp)





  
  

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[1] "ME"       "symptoms" "benefit"  "HIST"     "BSE"      "DECT"    





  
  

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> mtree <- ctree(ME ~ ., data = mammoexp)





  
  

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> stopifnot(isequal(predict(mtree), predict(mtree, newdata = mammoexp)))





  
  

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> stopifnot(isequal(predict(mtree), predict(mtree, newdata = mammoexp)))





  
  

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> 





  
  

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> proc.time()





  
  

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   user  system elapsed 





  
  

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   1.60    0.06    1.66