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Merge pull request #2 from prise6/fix-cran1

Fix cran1
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@ -3,4 +3,5 @@
^data-raw$ ^data-raw$
^draft$ ^draft$
^NEWS$ ^NEWS$
^cran-comments.md$ ^cran-comments.md$
^revdep$

1
.gitignore vendored
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@ -3,3 +3,4 @@
.RData .RData
/drafts/* /drafts/*
inst/doc inst/doc
/revdep/.cache.rds

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@ -1,11 +1,11 @@
Package: aVirtualTwins Package: aVirtualTwins
Type: Package Type: Package
Title: Adaptation of Virtual Twins Method from Jared Foster Title: Adaptation of Virtual Twins Method from Jared Foster
Version: 1.0.0.9000 Version: 1.0.1
Date: 2016-10-09 Date: 2018-02-03
Authors@R: person("Francois", "Vieille", email = "vieille.francois@gmail.com", Authors@R: c(person("Francois", "Vieille", email = "vieille.francois@gmail.com",
role = c("aut", "cre")) 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. 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 License: GPL-3 | file LICENSE
URL: https://github.com/prise6/aVirtualTwins URL: https://github.com/prise6/aVirtualTwins
BugReports: https://github.com/prise6/aVirtualTwins/issues BugReports: https://github.com/prise6/aVirtualTwins/issues
@ -18,7 +18,9 @@ Imports:
Suggests: Suggests:
caret, caret,
knitr, knitr,
rpart.plot rpart.plot,
rmarkdown,
e1071
Depends: Depends:
R (>= 3.2.0), R (>= 3.2.0),
Collate: Collate:
@ -42,4 +44,4 @@ Collate:
'tree.reg.R' 'tree.reg.R'
'tree.wrapper.R' 'tree.wrapper.R'
VignetteBuilder: knitr VignetteBuilder: knitr
RoxygenNote: 5.0.1 RoxygenNote: 6.0.1

7
NEWS
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@ -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) aVirtualTwins 1.0.0.9000 (2016-10-10)
---------------------------------------------------------------- ----------------------------------------------------------------

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@ -10,15 +10,8 @@
#' \code{\link{vt.tree}} is users function. #' \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 #' @docType package
#' @name aVirtualTwins #' @name aVirtualTwins

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

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

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

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

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

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

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

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@ -1,6 +1,6 @@
# aVirtualTwins # 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) 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)

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@ -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 This is the first submission
---------------------------------------------------------------- ----------------------------------------------------------------

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

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

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

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

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

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

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

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

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

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

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@ -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 subgroup is defined with the \emph{lower} event rate (survival = 1) in
treatement arm. treatement arm.
} }

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

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

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

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

5
revdep/check.R Normal file
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@ -0,0 +1,5 @@
library("devtools")
revdep_check()
revdep_check_save_summary()
revdep_check_print_problems()

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