Merge pull request #2 from prise6/fix-cran1

Fix cran1

.Rbuildignore

@@ -3,4 +3,5 @@
 ^data-raw$
 ^draft$
 ^NEWS$
-^cran-comments.md$
+^cran-comments.md$
+^revdep$

.gitignore

@@ -3,3 +3,4 @@
 .RData
 /drafts/*
 inst/doc
+/revdep/.cache.rds

DESCRIPTION

@@ -1,11 +1,11 @@
 Package: aVirtualTwins
 Type: Package
 Title: Adaptation of Virtual Twins Method from Jared Foster
-Version: 1.0.0.9000
-Date: 2016-10-09
-Authors@R: person("Francois", "Vieille", email = "vieille.francois@gmail.com",
-  role = c("aut", "cre"))
-Description: Research of subgroups in random clinical trials with binary outcome and two treatments groups. This is an adaptation of the Jared Foster method.
+Version: 1.0.1
+Date: 2018-02-03
+Authors@R: c(person("Francois", "Vieille", email = "vieille.francois@gmail.com",
+  role = c("aut", "cre")), person("Jared", "Foster", email = "jared.foster@nih.gov", role = c("aut")))
+Description: Research of subgroups in random clinical trials with binary outcome and two treatments groups. This is an adaptation of the Jared Foster method (<https://www.ncbi.nlm.nih.gov/pubmed/21815180>).
 License: GPL-3 | file LICENSE
 URL: https://github.com/prise6/aVirtualTwins
 BugReports: https://github.com/prise6/aVirtualTwins/issues
@@ -18,7 +18,9 @@ Imports:
 Suggests:
     caret,
     knitr,
-    rpart.plot
+    rpart.plot,
+    rmarkdown,
+    e1071
 Depends:
     R (>= 3.2.0),
 Collate:
@@ -42,4 +44,4 @@ Collate:
     'tree.reg.R'
     'tree.wrapper.R'
 VignetteBuilder: knitr
-RoxygenNote: 5.0.1
+RoxygenNote: 6.0.1

NEWS

@@ -1,3 +1,10 @@
+aVirtualTwins 1.0.1 (2018-01-30)
+----------------------------------------------------------------
+
+* Fix CRAN warning : CRAN packages using undeclared packages in vignettes
+* waiting for submission approval
+
+
 aVirtualTwins 1.0.0.9000 (2016-10-10)
 ----------------------------------------------------------------
 

R/aVirtualTwins.R

@@ -10,15 +10,8 @@
 #'  \code{\link{vt.tree}} is users function.
 #' }
 #'  
-#' @section TODO LIST:
-#' \emph{last update : 27.07.2015}
-#' \itemize{
-#'  \item More detailed documentation and vignettes 
-#'  \item Write examples
-#'  \item ...
-#' }
 #' 
-#' See github.com/prise6/aVirtualTwins for last updates.
+#' See http://github.com/prise6/aVirtualTwins for last updates.
 #'
 #' @docType package
 #' @name aVirtualTwins

R/forest.wrapper.R

@@ -32,23 +32,24 @@
 #' @return \code{VT.difft}
 #'  
 #' @examples
-#' \dontrun{
-#'  # data(sepsis)
-#'  vt.o <- vt.data(sepsis, "survival", "THERAPY", T)
-#'  # inside model : 
-#'  vt.f <- vt.forest("one", vt.o)
-#'  # ... 
-#'  # your model : 
-#'  rf <- randomForest(y = vt.o$getY(),
-#'                      x = vt.o$getX(int = T),
-#'                      mtry = 3,
-#'                      nodesize = 15)
-#'  vt.f <- vt.forest("one", vt.o, model = rf)
-#'  # ...
-#'  # Can also use ... parameters
-#'  vt.f <- vt.forest("one", vt.o, mtry = 3, nodesize = 15)
-#'  # ...
-#' }   
+#' 
+#' data(sepsis)
+#' vt.o <- vt.data(sepsis, "survival", "THERAPY", T)
+#' # inside model :
+#' vt.f <- vt.forest("one", vt.o)
+#' # ...
+#' # your model :
+#' # library(randomForest)
+#' # rf <- randomForest(y = vt.o$getY(),
+#' #                    x = vt.o$getX(int = T),
+#' #                    mtry = 3,
+#' #                    nodesize = 15)
+#' # vt.f <- vt.forest("one", vt.o, model = rf)
+#' # ...
+#' # Can also use ... parameters
+#' vt.f <- vt.forest("one", vt.o, mtry = 3, nodesize = 15)
+#' # ...
+#'    
 #' 
 #' @include forest.R difft.R
 #'   

R/formatRCTDataset.R

@@ -25,8 +25,11 @@
 #' 
 #' @examples
 #' \dontrun{
-#' data.format <- formatRCTDataset(data, "outcome", "treatment", TRUE)
-#' } 
+#'     data.format <- formatRCTDataset(data, "outcome", "treatment", TRUE)
+#' }
+#' data(sepsis)
+#' data.format <- formatRCTDataset(sepsis, "survival", "THERAPY", T)
+#'  
 #'
 #'  
 #'   

R/object.wrapper.R

@@ -13,18 +13,19 @@
 #' @param ... parameters of \code{\link{VT.object}}
 #'   
 #' @examples
-#' \dontrun{
-#'  data(sepsis)
-#'  formatRCTdataset(sepsis, "survival", "THERAPY", T)
-#' }
+#' 
+#' data(sepsis)
+#' vt.o <- vt.data(sepsis, "survival", "THERAPY", T)
 #'   
 #' @return \code{VT.object}
 #'   
-#' @include object.R
+#' @include object.R 
 #'   
 #' @name vt.data
 #'   
 #' @export vt.data
+#' 
+#' @seealso \code{\link{formatRCTDataset}}
 
 vt.data <- function(dataset, outcome.field, treatment.field, interactions = TRUE, ...){
   data <- formatRCTDataset(dataset, outcome.field, treatment.field, interactions = TRUE)

R/tools.R

@@ -18,18 +18,16 @@
 #' @return data.frame of rules
 #'   
 #' @examples 
-#' \dontrun{
-#'  # data(sepsis)
-#'  vt.o <- vt.data(sepsis, "survival", "THERAPY", T)
-#'  # inside model :
-#'  vt.f <- vt.forest("one", vt.o)
-#'  # use classification tree
-#'  vt.tr <- vt.tree("class", vt.f, threshold = c(0.01, 0.05))
-#'  # show subgroups
-#'  vt.subgroups(vt.tr)
-#'  # change options you'll be surprised !
-#'  vt.subgroups(vt.tr, verbose = T, tables = T) 
-#' }
+#' data(sepsis)
+#' vt.o <- vt.data(sepsis, "survival", "THERAPY", TRUE)
+#' # inside model :
+#' vt.f <- vt.forest("one", vt.o)
+#' # use classification tree
+#' vt.tr <- vt.tree("class", vt.f, threshold = c(0.01, 0.05))
+#' # show subgroups
+#' subgroups <- vt.subgroups(vt.tr)
+#' # change options you'll be surprised !
+#' subgroups <- vt.subgroups(vt.tr, verbose = TRUE, tables = TRUE)
 #' 
 #' @export vt.subgroups
 #'   
@@ -43,7 +41,7 @@ vt.subgroups <- function(vt.trees, only.leaf = T, only.fav = T, tables = F, verb
     unique(do.call(rbind, subgroups))
   }
   else{
-    subgroups <- vt.tree$getRules(only.leaf = only.leaf, only.fav = only.fav, tables = tables, verbose = verbose, compete = compete)
+    subgroups <- vt.trees$getRules(only.leaf = only.leaf, only.fav = only.fav, tables = tables, verbose = verbose, compete = compete)
   }
 }
 
@@ -62,21 +60,27 @@ vt.getQAOriginal <- function(response, trt, ahat){
 }
 
 vt.getTable <- function(table){
-  if(is.list(table)) table <-  table[[1]]
-  Incidence <- function(X) as.character(round(X[2] / X[3], digits = 3))
+  if(is.list(table)) table <- table[[1]]
+  Incidence <- function(X) round(X[2] / X[3], digits = 3)
   t <- stats::addmargins(table, margin = c(1,2), FUN = sum, quiet = T)
   t <- stats::addmargins(t, FUN = Incidence, margin = 1, quiet = T)
-  rr <- as.numeric(t["Incidence", "1"]) / as.numeric(t["Incidence", "0"])
+  rr <- NA_real_
+  if(nrow(t) == 4) rr <- t[4, 2] / t[4, 1]
   return(list(table = t, rr = rr))
 }
 
 vt.getIncidence <- function(df){
   if (nrow(df) == 0) table.res <- NULL
+  if (ncol(df) != 2) table.res <- NULL
   else{
-    table.res <- vt.getTable(table(df[, 1],
-                                   df[, 2],
-                                   deparse.level = 2,
-                                   dnn = c("resp", "trt")))
+    table.res <- vt.getTable(
+      table(
+        factor(df[, 1], levels = c(0, 1)),
+        factor(df[, 2], levels = c(0, 1)),
+        deparse.level = 2,
+        dnn = c("resp", "trt")
+      )
+    )
   }
   return(table.res)
 }

R/tree.R

@@ -248,17 +248,17 @@ VT.tree <- setRefClass(
           
           if(isTRUE(tables)){
             cat("\n")
-            cat(sprintf("Incidence dans la selection \n"))
+            cat(sprintf("Incidence in selection \n"))
             print(incid$table.selected$table)
             cat("\n")
-            cat(sprintf("Risque relatif (resub) : %0.3f \n", incid$table.selected$rr))
-            cat(sprintf("Risque relatif (snd) : %0.3f \n\n", incid$table.selected$rr.snd))
+            cat(sprintf("Relative risk (resub) : %0.3f \n", incid$table.selected$rr))
+            cat(sprintf("Relative risk (snd) : %0.3f \n\n", incid$table.selected$rr.snd))
             
-            cat(sprintf("Incidence dans le complementaire\n"))
+            cat(sprintf("Incidence in complement\n"))
             print(incid$table.not.selected$table)
             cat("\n")
-            cat(sprintf("Risque relatif (resub) : %0.3f \n", incid$table.not.selected$rr))
-            cat(sprintf("Risque relatif (snd) : %0.3f \n\n", incid$table.not.selected$rr.snd))
+            cat(sprintf("Relative risk (resub) : %0.3f \n", incid$table.not.selected$rr))
+            cat(sprintf("Relative risk (snd) : %0.3f \n\n", incid$table.not.selected$rr.snd))
           }
           
           cat("\n\n")
@@ -310,15 +310,15 @@ VT.tree <- setRefClass(
         table.A <- table.inc$table.selected
         table.A.cmpl <- table.inc$table.not.selected
         
-        cat(sprintf("Incidence dans le sous groupe A\n"))
+        cat(sprintf("Incidence in subgroup A\n"))
         print(table.A$table)
         cat("\n")
-        cat(sprintf("Risque relatif : %0.3f \n\n", table.A$risque_relatif))
+        cat(sprintf("Relative risk : %0.3f \n\n", table.A$risque_relatif))
         
-        cat(sprintf("Incidence dans le sous groupe A complementaire\n"))
+        cat(sprintf("Incidence in complement subgroup of A\n"))
         print(table.A.cmpl$table)
         cat("\n")
-        cat(sprintf("Risque relatif : %0.3f \n\n", table.A.cmpl$risque_relatif))
+        cat(sprintf("Relative risk : %0.3f \n\n", table.A.cmpl$risque_relatif))
       }else{
         return("Empty set")
       }

R/tree.class.R

@@ -11,7 +11,7 @@
 #' @export VT.tree.class
 #' 
 #' @import methods 
-#' @importFrom rpart rpart
+#' 
 VT.tree.class <- setRefClass(
   Class = "VT.tree.class",
   

R/tree.wrapper.R

@@ -24,21 +24,21 @@
 #'   dimension. See examples.
 #'   
 #' @examples
-#' \dontrun{
-#'  # data(sepsis)
-#'  vt.o <- vt.data(sepsis, "survival", "THERAPY", T)
-#'  # inside model : 
-#'  vt.f <- vt.forest("one", vt.o)
-#'  # use classification tree
-#'  vt.tr <- vt.tree("class", vt.f, threshold = c(0.01, 0.05))
-#'  # return a list
-#'  class(vt.tr)
-#'  # access one of the tree
-#'  vt.tr$tree1
-#'  # return infos
-#'  vt.tr$tree1$getInfos()
-#'  # ...
-#' }
+#' data(sepsis)
+#' vt.o <- vt.data(sepsis, "survival", "THERAPY", T)
+#' # inside model :
+#' vt.f <- vt.forest("one", vt.o)
+#' # use classification tree
+#' vt.tr <- vt.tree("class", vt.f, threshold = c(0.01, 0.05))
+#' # return a list
+#' class(vt.tr)
+#' # access one of the tree
+#' tree1 <- vt.tr$tree1
+#' # return infos
+#' # vt.tr$tree1$getInfos()
+#' # vt.tr$tree1$getRules()
+#' # use vt.subgroups tool:
+#' subgroups <- vt.subgroups(vt.tr)
 #'   
 #' @include tree.R
 #'   

README.md

@@ -1,6 +1,6 @@
 # aVirtualTwins
 
-[![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/aVirtualTwins)](http://cran.r-project.org/package=aVirtualTwins)
+[![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/aVirtualTwins)](https://cran.r-project.org/package=aVirtualTwins)
 
 An adaptation of VirtualTwins method from [Foster, J. C., Taylor, J. M.G. and Ruberg, S. J. (2011)](http://onlinelibrary.wiley.com/doi/10.1002/sim.4322/abstract)
 

cran-comments.md

@@ -1,3 +1,80 @@
+submission 4
+
+----------------------------------------------------------------
+
+## v1.0.1 : patch to cran fix minor issues:
+
+* make checkable examples : fix subgroups example
+
+## Test environments
+
+* Linux, Debian jessie, R 3.4.3
+* win-builder (devel and release)
+
+
+## R CMD check result
+
+Status: OK
+
+R CMD check results
+0 errors | 0 warnings | 0 notes
+
+
+This is the third submission
+
+----------------------------------------------------------------
+
+## v1.0.1 : patch to cran fix minor issues:
+
+* make checkable examples
+* update version date
+* add reference to Jared Foster article
+
+## Test environments
+
+* Linux, Debian jessie, R 3.4.3
+* win-builder (devel and release)
+
+
+## R CMD check result
+
+Status: OK
+
+R CMD check results
+0 errors | 0 warnings | 0 notes
+
+
+
+This is the second submission
+
+----------------------------------------------------------------
+
+## v1.0.1 : patch to cran warning:
+
+>CRAN packages using undeclared packages in vignettes
+
+`rmarkdown` seems to be the issue. Added `rmarkdown` to suggest field.
+`e1071` was added too.
+
+## Test environments
+
+* Linux, Debian jessie, R 3.4.3
+* win-builder (devel and release)
+
+
+## R CMD check result
+
+Status: OK
+
+R CMD check results
+0 errors | 0 warnings | 0 notes
+
+
+
+
+
+
+
 This is the first submission
 
 ----------------------------------------------------------------

man/VT.difft.Rd

@@ -33,13 +33,14 @@ So \emph{absolute} method is :
 
 \item{\code{difft}}{vector of difference between twin1 and twin2}
 }}
+
 \section{Methods}{
 
 \describe{
 \item{\code{computeDifft()}}{Compute difference between twin1 and twin2. See details.}
 }}
+
 \seealso{
 \code{\link{VT.forest}}, \code{\link{VT.forest.one}},
   \code{\link{VT.forest.double}}
 }
-

man/VT.forest-abstract.Rd

@@ -14,6 +14,7 @@ An abstract reference class to compute twin via random forests
 \describe{
 \item{\code{...}}{see fields of \code{\link{VT.difft}}}
 }}
+
 \section{Methods}{
 
 \describe{
@@ -23,7 +24,7 @@ An abstract reference class to compute twin via random forests
 
 \item{\code{run()}}{Compute twin1 and twin2 estimation. Switch treatment if necessary.}
 }}
+
 \seealso{
 \code{\link{VT.difft}}, \code{\link{VT.forest.one}}, \code{\link{VT.forest.double}}
 }
-

man/VT.forest.double.Rd

@@ -31,6 +31,7 @@ This is what \code{computeTwin2()} does.
 
 \item{\code{...}}{field from parent class : \code{\link{VT.forest}}}
 }}
+
 \section{Methods}{
 
 \describe{
@@ -38,8 +39,8 @@ This is what \code{computeTwin2()} does.
 
 \item{\code{computeTwin2()}}{Compute twin2 by the other part of data in the other forest. See details.}
 }}
+
 \seealso{
 \code{\link{VT.difft}}, \code{\link{VT.forest}},
   \code{\link{VT.forest.one}}
 }
-

man/VT.forest.fold.Rd

@@ -28,13 +28,14 @@ interactions}
 
 \item{\code{...}}{field from parent class : \code{\link{VT.forest}}}
 }}
+
 \section{Methods}{
 
 \describe{
 \item{\code{run()}}{Compute twin1 and twin2 estimation. Switch treatment if necessary.}
 }}
+
 \seealso{
 \code{\link{VT.difft}}, \code{\link{VT.forest}}, 
   \code{\link{VT.forest.one}}, \code{\link{VT.forest.double}}
 }
-

man/VT.forest.one.Rd

@@ -24,6 +24,7 @@ what \code{computeTwin1()} and \code{computeTwin2()} functions do.
 
 \item{\code{...}}{field from parent class : \code{\link{VT.forest}}}
 }}
+
 \section{Methods}{
 
 \describe{
@@ -31,7 +32,7 @@ what \code{computeTwin1()} and \code{computeTwin2()} functions do.
 
 \item{\code{computeTwin2()}}{Compute twin2 by switching treatment and applying random forest model}
 }}
+
 \seealso{
 \code{\link{VT.difft}}, \code{\link{VT.forest}}, \code{\link{VT.forest.double}}
 }
-

man/VT.object.Rd

@@ -33,6 +33,7 @@ treatments.}
 \item{\code{type}}{Character : binary or continous. Only binary is currently 
 available.}
 }}
+
 \section{Methods}{
 
 \describe{
@@ -53,6 +54,7 @@ If trt is not NULL, return predictors for T = trt}
 
 \item{\code{switchTreatment()}}{Switch treatment value.}
 }}
+
 \examples{
 \dontrun{
 # Default use :
@@ -78,4 +80,3 @@ vt.o$getIncidences()
 \seealso{
 \code{\link{VT.difft}}
 }
-

man/VT.predict.Rd

@@ -3,10 +3,10 @@
 \docType{methods}
 \name{VT.predict}
 \alias{VT.predict}
-\alias{VT.predict,RandomForest,data.frame,character-method}
 \alias{VT.predict,RandomForest,missing,character-method}
-\alias{VT.predict,randomForest,data.frame,character-method}
+\alias{VT.predict,RandomForest,data.frame,character-method}
 \alias{VT.predict,randomForest,missing,character-method}
+\alias{VT.predict,randomForest,data.frame,character-method}
 \alias{VT.predict,train,ANY,character-method}
 \alias{VT.predict,train,missing,character-method}
 \title{VT.predict generic function}

man/VT.tree-abstract.Rd

@@ -52,6 +52,7 @@ screening field}
 
 \item{\code{Ahat}}{vector Indicator of beglonging to Ahat}
 }}
+
 \section{Methods}{
 
 \describe{
@@ -74,7 +75,7 @@ screening field}
 
 \item{\code{run(...)}}{Compute tree with rpart parameters}
 }}
+
 \seealso{
 \code{\link{VT.tree.reg}}, \code{\link{VT.tree.class}}
 }
-

man/aVirtualTwins.Rd

@@ -4,6 +4,7 @@
 \name{aVirtualTwins}
 \alias{aVirtualTwins}
 \alias{aVirtualTwins-package}
+\alias{aVirtualTwins-package}
 \title{aVirtualTwins : An adapation of VirtualTwins method created by Jared Foster.}
 \description{
 aVirtualTwins is written mainly with reference classes. Briefly, there is three kinds of class :
@@ -15,15 +16,6 @@ aVirtualTwins is written mainly with reference classes. Briefly, there is three
  \code{\link{vt.tree}} is users function.
 }
 }
-\section{TODO LIST}{
-
-\emph{last update : 27.07.2015}
-\itemize{
- \item More detailed documentation and vignettes 
- \item Write examples
- \item ...
+\details{
+See http://github.com/prise6/aVirtualTwins for last updates.
 }
-
-See github.com/prise6/aVirtualTwins for last updates.
-}
-

man/formatRCTDataset.Rd

@@ -37,10 +37,12 @@ running VirtualTwins with interaction, it creates dummy variables.
 }
 \examples{
 \dontrun{
-data.format <- formatRCTDataset(data, "outcome", "treatment", TRUE)
-} 
+    data.format <- formatRCTDataset(data, "outcome", "treatment", TRUE)
+}
+data(sepsis)
+data.format <- formatRCTDataset(sepsis, "survival", "THERAPY", T)
+ 
 
  
   
 }
-

man/sepsis.Rd

@@ -43,4 +43,3 @@ True subgroup is \emph{PRAPACHE <= 26 & AGE <= 49.80}. \emph{NOTE:} This
 subgroup is defined with the \emph{lower} event rate (survival = 1) in
 treatement arm.
 }
-

man/vt.data.Rd

@@ -27,10 +27,11 @@ interactions, set to TRUE (default value)}
 a VT.object object.
 }
 \examples{
-\dontrun{
- data(sepsis)
- formatRCTdataset(sepsis, "survival", "THERAPY", T)
-}
+
+data(sepsis)
+vt.o <- vt.data(sepsis, "survival", "THERAPY", T)
   
 }
-
+\seealso{
+\code{\link{formatRCTDataset}}
+}

man/vt.forest.Rd

@@ -50,23 +50,23 @@ Is only used with forest.type = "fold". Default to 5. See
 parameter forest.type, any of these class can be used with its own parameter.
 }
 \examples{
-\dontrun{
- # data(sepsis)
- vt.o <- vt.data(sepsis, "survival", "THERAPY", T)
- # inside model : 
- vt.f <- vt.forest("one", vt.o)
- # ... 
- # your model : 
- rf <- randomForest(y = vt.o$getY(),
-                     x = vt.o$getX(int = T),
-                     mtry = 3,
-                     nodesize = 15)
- vt.f <- vt.forest("one", vt.o, model = rf)
- # ...
- # Can also use ... parameters
- vt.f <- vt.forest("one", vt.o, mtry = 3, nodesize = 15)
- # ...
-}   
+
+data(sepsis)
+vt.o <- vt.data(sepsis, "survival", "THERAPY", T)
+# inside model :
+vt.f <- vt.forest("one", vt.o)
+# ...
+# your model :
+# library(randomForest)
+# rf <- randomForest(y = vt.o$getY(),
+#                    x = vt.o$getX(int = T),
+#                    mtry = 3,
+#                    nodesize = 15)
+# vt.f <- vt.forest("one", vt.o, model = rf)
+# ...
+# Can also use ... parameters
+vt.f <- vt.forest("one", vt.o, mtry = 3, nodesize = 15)
+# ...
+   
 
 }
-

man/vt.subgroups.Rd

@@ -32,18 +32,15 @@ Function which uses \code{\link{VT.tree}} intern functions. Package
 rpart.plot must be loaded. See \code{\link{VT.tree}} for details.
 }
 \examples{
-\dontrun{
- # data(sepsis)
- vt.o <- vt.data(sepsis, "survival", "THERAPY", T)
- # inside model :
- vt.f <- vt.forest("one", vt.o)
- # use classification tree
- vt.tr <- vt.tree("class", vt.f, threshold = c(0.01, 0.05))
- # show subgroups
- vt.subgroups(vt.tr)
- # change options you'll be surprised !
- vt.subgroups(vt.tr, verbose = T, tables = T) 
-}
+data(sepsis)
+vt.o <- vt.data(sepsis, "survival", "THERAPY", TRUE)
+# inside model :
+vt.f <- vt.forest("one", vt.o)
+# use classification tree
+vt.tr <- vt.tree("class", vt.f, threshold = c(0.01, 0.05))
+# show subgroups
+subgroups <- vt.subgroups(vt.tr)
+# change options you'll be surprised !
+subgroups <- vt.subgroups(vt.tr, verbose = TRUE, tables = TRUE)
 
 }
-

man/vt.tree.Rd

@@ -39,21 +39,20 @@ See \code{\link{VT.tree}}, \code{\link{VT.tree.class}} and
 \code{\link{VT.tree.reg}} classes.
 }
 \examples{
-\dontrun{
- # data(sepsis)
- vt.o <- vt.data(sepsis, "survival", "THERAPY", T)
- # inside model : 
- vt.f <- vt.forest("one", vt.o)
- # use classification tree
- vt.tr <- vt.tree("class", vt.f, threshold = c(0.01, 0.05))
- # return a list
- class(vt.tr)
- # access one of the tree
- vt.tr$tree1
- # return infos
- vt.tr$tree1$getInfos()
- # ...
-}
+data(sepsis)
+vt.o <- vt.data(sepsis, "survival", "THERAPY", T)
+# inside model :
+vt.f <- vt.forest("one", vt.o)
+# use classification tree
+vt.tr <- vt.tree("class", vt.f, threshold = c(0.01, 0.05))
+# return a list
+class(vt.tr)
+# access one of the tree
+tree1 <- vt.tr$tree1
+# return infos
+# vt.tr$tree1$getInfos()
+# vt.tr$tree1$getRules()
+# use vt.subgroups tool:
+subgroups <- vt.subgroups(vt.tr)
   
 }
-

revdep/check.R

@@ -0,0 +1,5 @@
+library("devtools")
+
+revdep_check()
+revdep_check_save_summary()
+revdep_check_print_problems()