could not find function "rfsrc"

The error message "could not find function 'rfsrc'" usually indicates that the randomForestSRC package is not installed or loaded in R.

To fix this issue, you can try installing the randomForestSRC package using the following command:

install.packages("randomForestSRC")

Once the package is installed, you can load it into your R session using the following command:

library(randomForestSRC)

This should allow you to use the "rfsrc" function without any issues.

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could not find function "timeROC"

The error message "could not find function" usually means that the function you are trying to use is not available in the current environment.

In this case, it seems that you are trying to use the function "timeROC" which is not recognized by R. It's possible that this function is not part of any package you have installed or it could be a custom function that you or someone else has created.

To solve this issue, you can try the following steps:

1. Check if you have loaded the package that contains the "timeROC" function using the library() function. If not, load the package using library().

2. If you don't have the package installed, you can install it using install.packages() function.

3. If the function is a custom function, make sure that you have defined it properly in your R script or import it from the file where it is defined.

4. If none of the above steps work, you can search for the function online or consult the documentation of the package or the function creator for more information.

could not find function "ddply"

The error message "could not find function 'ddply'" usually occurs when the 'plyr' package is not installed or loaded in R. The 'ddply' function is a part of the 'plyr' package, which stands for "split", "apply", and "combine" operations on data frames.

To resolve this error, you can try installing the 'plyr' package by running the following command:

install.packages("plyr")

After installation, you can load the package using the library() function:

library(plyr)

This should make the 'ddply' function available for use in your R session.