Disregarding simple warnings/errors in tryCatch()

Question

I\'m a huge fan of tryCatch(). However, until today I never really paid attention to the distinction between simple and regular warnings/errors and thus I don\'

Answer 1

I think you're looking for the difference between tryCatch, which catches a condition and continues evaluation from the environment where the tryCatch was defined, versus withCallingHandlers, which allows you to 'handle' a condition and then continue on from the location where the condition occurred. Take a look at warning (or the help page for warning, but that's less fun), especially the lines

    withRestarts({
        .Internal(.signalCondition(cond, message, call))
        .Internal(.dfltWarn(message, call))
    }, muffleWarning = function() NULL)

This says -- signal a condtion, but insert a 'restart' where the condition was signaled from. Then you'd

withCallingHandlers({
    warning("curves ahead")
    2
}, warning = function(w) {
    ## what are you going to do with the warning?
    message("warning occurred: ", conditionMessage(w))
    invokeRestart("muffleWarning")
})

Although withCallingHandlers is often used with warnings and tryCatch with errors, there is nothing to stop one from 'handling' an error or catching a warning if that is the appropriate action.

Answer 2

You can recall the forecast within the warning section, something like this:

mod <- tryCatch(
  out <- forecast::auto.arima(x=y),
  error=function(e) {
    print(e)
  },
  warning=function(w) {
    print(w)
    out <- forecast::auto.arima(x=y)
    return(out)
  }
)

This will print a warning , but the result of forecast is stored in mod now.

<simpleWarning in kpss.test(x): p-value smaller than printed p-value>
> mod
Series: y 
ARIMA(4,1,1)                    

Coefficients:
         ar1      ar2     ar3      ar4      ma1
      0.6768  -0.2142  0.5025  -0.7125  -0.8277
s.e.  0.0749   0.0889  0.0874   0.0735   0.0485

sigma^2 estimated as 915556:  log likelihood=-780.33
AIC=1572.65   AICc=1573.62   BIC=1587.91