[R] Continuing on with a loop when there's a failure

[David Winsemius]

On Jul 13, 2010, at 9:04 AM, David Winsemius wrote:

>
> On Jul 13, 2010, at 8:47 AM, Josh B wrote:
>
>> Thanks again, David.
>>
>> ...but, alas, I still can't get it work!

(BTW, it did work.)

>> Here's what I'm trying now:
>>
>> for (i in 1:2) {
>>    mod.poly3 <- try(lrm(x[,i] ~ pol(x1, 3) + pol(x2, 3), data=x))
>>    results[1,i] <- anova(mod.poly3)[1,3]
>> }
>
> You need to do some programming.

(Or I suppose you could wrap both the lrm and the anova calls in try.)

> You did not get an error from the lrm but rather from the anova call  
> because you tried to give the results of the try function to anova  
> without first checking to see if an error had occurred.
>
> -- 
> David.
>>
>> Here's what happens (from the console):
>>
>> Error in fitter(X, Y, penalty.matrix = penalty.matrix, tol = tol,  
>> weights = weights,  :
>>  NA/NaN/Inf in foreign function call (arg 1)
>> Error in UseMethod("anova") :
>>  no applicable method for 'anova' applied to an object of class  
>> "try-error"
>>
>> ...so I still can't make my results matrix. Could I ask you for  
>> some specific code to make this work? I'm not that familiar with  
>> the syntax for try or tryCatch, and the help files for them are  
>> pretty bad, in my humble opinion.
>>
>> I should clarify that I actually don't care about the failed runs  
>> per se. I just want R to keep going in spite of them and give me my  
>> results matrix.
>>
>> From: David Winsemius <dwinsemius at comcast.net>
>> To: Josh B <joshb41 at yahoo.com>
>> Cc: R Help <r-help at r-project.org>
>> Sent: Mon, July 12, 2010 8:09:03 PM
>> Subject: Re: [R] Continuing on with a loop when there's a failure
>>
>>
>> On Jul 12, 2010, at 6:18 PM, Josh B wrote:
>>
>> > Hi R sages,
>> >
>> > Here is my latest problem. Consider the following toy example:
>> >
>> > x <- read.table(textConnection("y1 y2 y3 x1 x2
>> > indv.1 bagels donuts bagels 4 6
>> > indv.2 donuts donuts donuts 5 1
>> > indv.3 donuts donuts donuts 1 10
>> > indv.4 donuts donuts donuts 10 9
>> > indv.5 bagels donuts bagels 0 2
>> > indv.6 bagels donuts bagels 2 9
>> > indv.7 bagels donuts bagels 8 5
>> > indv.8 bagels donuts bagels 4 1
>> > indv.9 donuts donuts donuts 3 3
>> > indv.10 bagels donuts bagels 5 9
>> > indv.11 bagels donuts bagels 9 10
>> > indv.12 bagels donuts bagels 3 1
>> > indv.13 donuts donuts donuts 7 10
>> > indv.14 bagels donuts bagels 2 10
>> > indv.15 bagels donuts bagels 9 6"), header = TRUE)
>> >
>> > I want to fit a logistic regression of y1 on x1 and x2. Then I  
>> want to run a
>> > logistic regression of y2 on x1 and x2. Then I want to run a  
>> logistic regression
>> > of y3 on x1 and x2. In reality I have many more Y columns than  
>> simply "y1,"
>> > "y2," and "y3," so I must design a loop. Notice that y2 is  
>> invariant and thus it
>> > will fail. In reality, some y columns will fail for much more  
>> subtle reasons.
>> > Simply screening my data to eliminate invariant columns will not  
>> eliminate the
>> > problem.
>> >
>> > What I want to do is output a piece of the results from each run  
>> of the loop to
>> > a matrix. I want the to try each of my y columns, and not give up  
>> and stop
>> > running simply because a particular y column is bad. I want it to  
>> give me "NA"
>> > or something similar in my results matrix for the bad y columns,  
>> but I want it
>> > to keep going give me good data for the good y columns.
>> >
>> > For instance:
>> > results <- matrix(nrow = 1, ncol = 3)
>> > colnames(results) <- c("y1", "y2", "y3")
>> >
>> > for (i in 1:2) {
>> > mod.poly3 <- lrm(x[,i] ~ pol(x1, 3) + pol(x2, 3), data=x)
>> > results[1,i] <- anova(mod.poly3)[1,3]
>> > }
>> >
>> > If I run this code, it gives up when fitting y2 because the y2 is  
>> bad. It
>> > doesn't even try to fit y3. Here's what my console shows:
>> >
>> >> results
>> >            y1 y2 y3
>> > [1,] 0.6976063 NA NA
>> >
>> > As you can see, it gave up before fitting y3, which would have  
>> worked.
>> >
>> > How do I force my code to keep going through the loop, despite  
>> the rotten apples
>> > it encounters along the way?
>>
>> ?try
>>
>> http://cran.r-project.org/doc/FAQ/R-FAQ.html#How-can-I-capture-or-ignore-errors-in-a-long-simulation_003f
>>
>> (Doesn't only apply to simulations.)
>>
>> > Exact code that gets the job done is what I am
>> > interested in. I am a post-doc -- I am not taking any classes. I  
>> promise this is
>> > not a homework assignment!
>>
>> --
>> David Winsemius, MD
>> West Hartford, CT
>>
>>
>>
>
> David Winsemius, MD
> West Hartford, CT
>
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David Winsemius, MD
West Hartford, CT