Dear all,
I am not sure I understand fully the functionality of "tryCatch" and
"try" commands and how these are used to continue a for/next loop if an
error occurs within the loop.
Can somebody point me to material (or share some code) with more
extensive examples than the ones in the help/FAQ pages?
Do explain my problem in more detail:
for (i in 100:1000)
{
## do some other stuff
dataset<-head(data,i)
tryCatch(estimatemodel(dataset))
}
My for/next loop reads in data (increasing the dataset by one point at
every loop run) and then estimates a model. When the problem is
computationally singular, the loop exits. I want to continue the loop
and register an "error" estimation value for that step. However when I
use use the try tryCatch(estimatemodel(data)) (where estimatemodel() is
a wrapper function calling the model estimation and optimization
routines), the problem still persists.
Is this the correct way to use tryCatch (or try) or should these go
inside the actual code bits (i.e., in a more low level fashion) that
conduct the optimization and model estimation?
Apologies if this is not clear enough.
Best,
Costas
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