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Josh B

2010-Jul-12 22:18 UTC

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

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? 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!

Thanks in advance,
-----------------------------------
Josh Banta, Ph.D
Center for Genomics and Systems Biology
New York University
100 Washington Square East
New York, NY 10003
Tel: (212) 998-8465
http://plantevolutionaryecology.org



      
	[[alternative HTML version deleted]]

David Winsemius

2010-Jul-13 00:09 UTC

head link

[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

Josh B

2010-Jul-18 08:25 UTC

head link

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

Hello Peter,

I tried your suggestion, but I was still not able to get it to work. Would you 
mind looking at my code again? Here's what I'm trying:

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)

results <- matrix(nrow = 1, ncol = 3)
colnames(results) <- c("y1", "y2", "y3")

for (i in 1:2) {
    mod.poly3 <- try(lrm(x[,i] ~ pol(x1, 3) + pol(x2, 3), data=x))
    if(class(mod.poly3) == 'try-error')
        {results[1,i] <- NA}
        else {mod.poly3 <- lrm(x[,i] ~ pol(x1, 3) + pol(x2, 3), data=x)
        results[1,i] <- anova(mod.poly3)[1,3]
    }
}


...and here's the output:
> results     y1 y2 y3
[1,] NA NA NA

The results matrix is empty!



________________________________
From: Peter Konings <peter.l.e.konings@gmail.com>

Sent: Tue, July 13, 2010 5:45:17 PM
Subject: Re: [R] Continuing on with a loop when there's a failure

Hi Josh,

Test the class of the resulting object. If it is 'try-error' fill your
result
with NA or do some other error handling.

result <- try(somemodel)
if(class(result) == 'try-error')
{
# some error handling
} else {
# whatever happens if the result is ok
}

HTH
Peter.




In my opinion the try and tryCatch commands are written and documented
rather>poorly. Thus I am not sure what to program exactly.
>
>For instance, I could query mod.poly3 and use an if/then statement to
proceed,
>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 <dwinsemius@comcast.net>
>To: David Winsemius <dwinsemius@comcast.net>
>
>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.
>>>
>[[elided Yahoo spam]]
>
>
>(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@comcast.net>
>
>
>>> 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
>>>
>>>f
>>>
>>> (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
>[[elided Yahoo spam]]
>
>>>
>>> --
>>> David Winsemius, MD
>>> West Hartford, CT
>>>
>>>
>>>
>>
>> David Winsemius, MD
>> West Hartford, CT
>>
>> ______________________________________________
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
>David Winsemius, MD
>West Hartford, CT
>
>
>
>
       [[alternative HTML version deleted]]>
>
>______________________________________________
>R-help@r-project.org mailing list
>https://stat.ethz.ch/mailman/listinfo/r-help
>PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>and provide commented, minimal, self-contained, reproducible code.
>


      
	[[alternative HTML version deleted]]

Josh B

2010-Jul-18 08:37 UTC

head link

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

Oops, forgot to add the line:

library(Design)

#the lrm function is in the Design library

...but even when I load the Design library, the loop still doesn't work. It 
stops after failing on the second run of the loop:
> results            y1 y2 y3
[1,] 0.6976063 NA NA

(The third run through the loop should have succeeded and left numeric output in
the matrix called "results", but it did not).



________________________________

To: Peter Konings <peter.l.e.konings@gmail.com>
Cc: R Help <r-help@r-project.org>
Sent: Sun, July 18, 2010 12:25:42 PM
Subject: Re: [R] Continuing on with a loop when there's a failure


Hello Peter,

I tried your suggestion, but I was still not able to get it to work. Would you 
mind looking at my code again? Here's what I'm trying:

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)

results <- matrix(nrow = 1,  ncol = 3)
colnames(results) <- c("y1", "y2", "y3")

for (i in 1:2) {
    mod.poly3 <- try(lrm(x[,i] ~ pol(x1, 3) + pol(x2, 3), data=x))
    if(class(mod.poly3) == 'try-error')
        {results[1,i] <- NA}
        else {mod.poly3 <- lrm(x[,i] ~ pol(x1, 3) + pol(x2, 3), data=x)
        results[1,i] <- anova(mod.poly3)[1,3]
    }
}


...and here's the output:
> results     y1 y2 y3
[1,] NA NA NA

[[elided Yahoo spam]]



________________________________
From: Peter Konings  <peter.l.e.konings@gmail.com>

Sent: Tue, July 13, 2010 5:45:17 PM
Subject: Re: [R] Continuing on with a loop when there's a failure

Hi Josh,

Test the class of the resulting object. If it is 'try-error' fill your
result
with NA or do some other error handling.

result <- try(somemodel)
if(class(result) == 'try-error')
{
# some error handling
} else {
# whatever happens if the result is ok
}

HTH
Peter.




In my opinion the try and tryCatch commands are written and documented
rather>poorly. Thus I am not sure what to program exactly.
>
>For instance, I could query mod.poly3 and use an if/then statement to
proceed,
>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 <dwinsemius@comcast.net>
>To: David Winsemius <dwinsemius@comcast.net>
>
>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.
>>>
>[[elided Yahoo spam]]
>
>
>(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@comcast.net>
>
>
>>> 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
>>>
>>>f
>>>
>>> (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
>[[elided Yahoo spam]]
>
>>>
>>> --
>>> David Winsemius, MD
>>> West Hartford, CT
>>>
>>>
>>>
>>
>> David Winsemius, MD
>> West Hartford, CT
>>
>> ______________________________________________
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
>David Winsemius, MD
>West Hartford, CT
>
>
>
>
       [[alternative HTML version deleted]]>
>
>______________________________________________
>R-help@r-project.org mailing list
>https://stat.ethz.ch/mailman/listinfo/r-help
>PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>and provide commented, minimal, self-contained, reproducible code.
>

      
	[[alternative HTML version deleted]]

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