From c36a3d8d37ca238ccfe538d457e87bb9d77233bd Mon Sep 17 00:00:00 2001 From: Joel Therrien Date: Fri, 5 Jul 2019 12:08:03 -0700 Subject: [PATCH] Small update to vignette --- vignettes/simple-example.Rmd | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/vignettes/simple-example.Rmd b/vignettes/simple-example.Rmd index b640268..196e981 100644 --- a/vignettes/simple-example.Rmd +++ b/vignettes/simple-example.Rmd @@ -55,7 +55,7 @@ We specify `splitFinder = LogRankSplitFinder(1:2, 2)`, which indicates that we h We specify that we want a forest of 100 trees (`ntree = 100`), that we want to try all possible splits when trying to split on a variable (`numberOfSplits = 0`), that we want to try splitting on two predictors at a time (`mtry = 2`), and that the terminal nodes should have an average size of at minimum 15 (`nodeSize = 15`; accomplished by not splitting any nodes with size less than 2 $\times$ `nodeSize`). `randomSeed = 15` specifies a seed so that the results are deterministic; note that **largeRCRF** generates random numbers separately from R and so is not affected by `set.seed()`. -Printing `model` on its own doesn't really do much except print the different components and parameters that made the forest. +Printing `model` on its own doesn't do much except print the different components and parameters that made the forest. ```{r} model @@ -67,7 +67,7 @@ Next we'll make predictions on the training data. Since we're using the training predictions <- predict(model) ``` -Since our data is competing risks data, our responses are several functions which can't really be printed on screen. Instead a message lets us know of several functions which can let us extract the estimate of the survivor curve, the cause-specific cumulative incidence functions, or the cause-specific cumulative hazard functions (CHF). +Since our data is competing risks data, our responses are several functions which can't be printed on screen. Instead a message lets us know of several functions which can let us extract the estimate of the survivor curve, the cause-specific cumulative incidence functions, or the cause-specific cumulative hazard functions (CHF). ```{r} predictions[[1]]