On Jul 13, 2010, at 9:24 AM, Josh B wrote:

In my opinion the try and tryCatch commands are written and documented rather poorly. Thus I am not sure what to program exactly.

Didn't you see the "silent" parameter? Its seems to be documented fairly clearly to me.

The testing of try at the console is not going to be very illuminating, since it really only has value within a function that you want to continue despite an error. try() WILL provide that facility but _you_ need to decide what you do with the information it returns, which in the case of its use with the default silent=FALSE is just the error message itself.



For instance, I could query mod.poly3 and use an if/then statement to proceed,

So why didn't you? A good result would be signaled by: "lrm" %in& class(mod.poly3)

--
David.

but querying mod.poly3 is weird. For instance, here's the output when it fails:

> mod.poly3 <- try(lrm(x[,2] ~ pol(x1, 3) + pol(x2, 3), data=x))
Error in fitter(X, Y, penalty.matrix = penalty.matrix, tol = tol, weights = weights, :
  NA/NaN/Inf in foreign function call (arg 1)
> mod.poly3
[1] "Error in fitter(X, Y, penalty.matrix = penalty.matrix, tol = tol, weights = weights, : \n NA/NaN/Inf in foreign function call (arg 1)\n"
attr(,"class")
[1] "try-error"

...and here's the output when it succeeds:
> mod.poly3 <- try(lrm(x[,1] ~ pol(x1, 3) + pol(x2, 3), data=x))
> mod.poly3

Logistic Regression Model

lrm(formula = x[, 1] ~ pol(x1, 3) + pol(x2, 3), data = x)


Frequencies of Responses
bagels donuts
    10      5

       Obs  Max Deriv Model L.R.       d.f.          P          C
        15      4e-04       3.37          6     0.7616       0.76
       Dxy      Gamma      Tau-a         R2      Brier          g
      0.52       0.52      0.248      0.279      0.183      1.411
        gr         gp
       4.1      0.261

          Coef     S.E.    Wald Z P
Intercept -5.68583 5.23295 -1.09  0.2772
x1         1.87020 2.14635  0.87  0.3836
x1^2      -0.42494 0.48286 -0.88  0.3788
x1^3       0.02845 0.03120  0.91  0.3618
x2         3.49560 3.54796  0.99  0.3245
x2^2      -0.94888 0.82067 -1.16  0.2476
x2^3       0.06362 0.05098  1.25  0.2121

...so what exactly would I query to design my if/then statement?

From: David Winsemius <dwinsem...@comcast.net>
To: David Winsemius <dwinsem...@comcast.net>
Cc: Josh B <josh...@yahoo.com>; R Help <r-help@r-project.org>
Sent: Tue, July 13, 2010 9:09:04 AM
Subject: Re: [R] Continuing on with a loop when there's a failure


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 <dwinsem...@comcast.net>
>> To: Josh B <josh...@yahoo.com>
>> Cc: R Help <r-help@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




David Winsemius, MD
West Hartford, CT

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