Add documentation and vignette

inst/doc/full-example.R

@@ -116,7 +116,10 @@ head(model.difft$difft)
 tr.class <- vt.tree("class",
                     vt.difft = vt.f.rf,
                     sens = ">",
-                    threshold = quantile(vt.f.rf$difft, seq(.5, .8, .1)))
+                    threshold = quantile(vt.f.rf$difft, seq(.5, .8, .1)),
+                    maxdepth = 3,
+                    cp = 0,
+                    maxcompete = 2) 
 # tr.class is a list if threshold is a vectoor
 class(tr.class)
 # acce trees with treeXX
@@ -130,6 +133,34 @@ tr.reg <- vt.tree("reg",
                   threshold = quantile(vt.f.rf$difft, seq(.5, .8, .1)))
 # tr.class is a list if threshold is a vectoor
 class(tr.reg)
-# acce trees with treeXX
+# access trees with treeXX
 class(tr.reg$tree1)
 
+## ------------------------------------------------------------------------
+# use tr.class computed previously
+vt.sbgrps <- vt.subgroups(tr.class)
+# print tables with knitr package
+library(knitr)
+knitr::kable(vt.sbgrps)
+
+## ---- echo=F, fig.align='center', fig.height=4, fig.width=6--------------
+library(rpart.plot)
+rpart.plot(tr.class$tree2$tree, type = 1, extra = 1)
+
+## ------------------------------------------------------------------------
+tr.class$tree2$createCompetitors()
+head(tr.class$tree2$competitors)
+
+## ------------------------------------------------------------------------
+vt.o$getIncidences("PRAPACHE >= 26 & AGE >= 52")
+# or
+# tr.class$tree2$getIncidences("PRAPACHE >= 26 & AGE >= 52")
+
+## ------------------------------------------------------------------------
+tr.class$tree2$getInfos()
+# access Ahat
+# tr.class$tree2$Ahat
+
+## ------------------------------------------------------------------------
+tr.class$tree2$run(maxdepth = 2)
+

inst/doc/full-example.Rmd

@@ -10,6 +10,18 @@ vignette: >
   %\VignetteEncoding{UTF-8}
 ---
 
+# Contents
+
+1. <a href="#introduction">Introduction</a>
+2. <a href="#quick-preview">Quick preview</a>
+3. <a href="#sepsis-dataset">Sepsis dataset</a>
+4. <a href="#create-object-virtualtwins">Create object virtual twins</a>
+5. <a href="#step-1-compute-hatp_1i-and-hatp_0i">Step 1 : compute probabilities</a>
+6. <a href="#step-2-estimate-a-regression-or-classification-tree">Step 2 : Estimate a decision tree</a>
+7. <a href="#subgroups-and-results">Subgroups and results</a>
+8. <a href="#questions">Questions</a>
+
+
 # Introduction
 
 The goal of this vignette is to show most of all possibilies with *aVT* (for *aVirtualTwins* meaning *a*daptation of *Virtual Twins* method) package. 
@@ -310,7 +322,7 @@ Anyway, aVirtualTwins package can be used. To do so, you can use `VT.difft()` cl
 
 * `vt.object` : return of `vt.data()` function
 * `twin1` : estimate of $P(Y_{i} = 1 | T = T_{i})$ : meaning response probability under the correct treatment.
-* `twin1` : estimate of $P(Y_{i} = 1 | T = 1-T_{i})$ : meaning response probability under the other treatment.
+* `twin2` : estimate of $P(Y_{i} = 1 | T = 1-T_{i})$ : meaning response probability under the other treatment.
 * `method` : _absolute_ (default), _relative_ or _logit_. See `?VT.difft` for details.
 
 ```{r}
@@ -360,7 +372,10 @@ See `?VT.tree` for details.
 tr.class <- vt.tree("class",
                     vt.difft = vt.f.rf,
                     sens = ">",
-                    threshold = quantile(vt.f.rf$difft, seq(.5, .8, .1)))
+                    threshold = quantile(vt.f.rf$difft, seq(.5, .8, .1)),
+                    maxdepth = 3,
+                    cp = 0,
+                    maxcompete = 2) 
 # tr.class is a list if threshold is a vectoor
 class(tr.class)
 # acce trees with treeXX
@@ -382,13 +397,80 @@ tr.reg <- vt.tree("reg",
                   threshold = quantile(vt.f.rf$difft, seq(.5, .8, .1)))
 # tr.class is a list if threshold is a vectoor
 class(tr.reg)
-# acce trees with treeXX
+# access trees with treeXX
 class(tr.reg$tree1)
 ```
 
+-----------
 
-## Subgroups and results
-
+# Subgroups and results
+
+Once trees have been computed, you surely want to see what are the subgroups. This package provides a wrapper function of intern methods of `VT.tree` class : `vt.subgroups()`.
+
+This function takes in argument : 
+
+* `vt.tree` : object or list of class `VT.tree`. Return of the `vt.tree()` function.
+* `only.leaf` : logical. Set `TRUE` (default) to visualize only terminal nodes.
+* `only.fav` : logical. Set `TRUE` (default) to visualize only class 1 nodes. ($\hat{A}$)
+* `tables` : logical. Set `FALSE` (default) to prevent tables of incidences from being printed.
+* `verbose` : logical. Set `FALSE` (default) to prevent detailed stuffs from being printed.
+* `compete` : logical. Set `TRUE` to print competitors rules thanks to competitors split. `FALSE` is default value.
+
+If `vt.tree` is a list, unique subgroups are printed.
+
+```{r}
+# use tr.class computed previously
+vt.sbgrps <- vt.subgroups(tr.class)
+# print tables with knitr package
+library(knitr)
+knitr::kable(vt.sbgrps)
+```
+
+You can plot one tree with package `rpart.plot`
+
+```{r, echo=F, fig.align='center', fig.height=4, fig.width=6}
+library(rpart.plot)
+rpart.plot(tr.class$tree2$tree, type = 1, extra = 1)
+```
+
+If you want to see competitors split : 
+
+```{r}
+tr.class$tree2$createCompetitors()
+head(tr.class$tree2$competitors)
+```
+
+If you want to print incidence of a subgroup :
+```{r}
+vt.o$getIncidences("PRAPACHE >= 26 & AGE >= 52")
+# or
+# tr.class$tree2$getIncidences("PRAPACHE >= 26 & AGE >= 52")
+```
+
+If you want to get infos about the tree
+
+```{r}
+tr.class$tree2$getInfos()
+# access Ahat
+# tr.class$tree2$Ahat
+```
+
+You can re-run rpart computation:  
+
+```{r}
+tr.class$tree2$run(maxdepth = 2)
+```
+
+Type `?VT.tree` for details.
+
+-----------
+
+# Questions
+
+This vignette is a bit messy right now, therefore feel free to ask anything to the repository issue reports : 
+
+1. https://github.com/prise6/aVirtualTwins
+2. read documentation with `?aVirtualTwins` 
 
 
 

man/vt.subgroups.Rd

@@ -20,6 +20,9 @@ favorable label of the tree). TRUE is default.}
 default.}
 
 \item{verbose}{print infos during computation. FALSE is default.}
+
+\item{compete}{print competitors rules thanks to competitors computation of
+  the tree}
 }
 \value{
 data.frame of rules