[R] Logical Indicator for Warning and Error Messages?

[David Winsemius]

On Jan 2, 2011, at 11:41 PM, David Crow wrote:

> Dear R Community-
>
>
>
> Is there a logical variable indicating the presence of a warning or  
> error
> message after executing a command?  I’m bootstrapping a logit model  
> (1,000
> iterations, relevant code posted below), but the model fails to  
> converge on
> many iterations.  (I’m guessing that a small sample size and the  
> combination
> of sampling with replacement, high item missingness, and list-wise  
> deletion
> leads to a sparse data problem for some iterations.)
>
>
>
> Even for the iterations that fail to converge, though, the program  
> produces
> parameter estimates.   I would like to remove these parameter  
> estimates from
> N x k matrix containing the boostrapped parameter estimates.  What I  
> was
> thinking of is adding a line of code to check if there is a warning  
> or error
> message present, recording the iteration numbers where there are
> error/warning messages, and replacing the parameters for those  
> iterations
> with NA’s.  I’ve checked the help pages for the “warning”,  
> “getOption”, and
> other commands, but it’s not immediately apparent to me how to check  
> for the
> presence of warning or error messages.

?options
#says that if "warn" is >= 2 that warnings are turned into errors
?try
# for handling of errors

-- 
David.

>
>
>
> Here’s the relevant portion of the code (I’ve omitted the parts that  
> recover
> parameter and fit estimates for each iteration):
>
>
>
> *************************************
>
> [Code Starts Here]
>
>
>
> #Create Objects
>
> N = 1000                               #1000 iterations
>
> set.seed(7843)
>
> seed = sample(10000000, 1000)
>
>
>
> #1000 Iterations
>
> for (i in 1:N){
>
>
>
> #Bootstap (Sampling with Replacement)
>
> set.seed(seed[i])
>
> pre <- subset(cainit, time==1)
>
> sampt1 <- sort(sample(nrow(pre), nrow(pre), replace=T))
>
> sampt1 <- pre[sampt1,]
>
>
>
>
>
> #T1 Model of Vote Intention
>
> try(T1A <- glm(prop1a ~ educ + age + inc + dem + appgov + appleg +  
> budget +
> co1a +
>
>                prop1b + prop1d,family=binomial(link="logit"),
>
>                data=sampt1, na.action=na.exclude))
>
>
>
> ##[NOTE:  the “lrm” command is part of the “Design” package]
>
> try(T1a <- lrm(prop1a ~ educ + age + inc + dem + appgov + appleg +  
> budget +
> co1a +
>
>                prop1b + prop1d, data=sampt1))
>
> }
>
>
>
> [Code Ends Here]
>
> ******************************************
>
>
>
>
>
>
>
> The following set of warning/error messages is repeated about a  
> dozen times
> at the end of the loop:
>
>
>
> Error in lrm(prop1a ~ educ + age + inc + dem + appgov + appleg +  
> budget +  :
>
>
>  Unable to fit model using “lrm.fit”
>
> In addition: Warning messages:
>
> 1: glm.fit: fitted probabilities numerically 0 or 1 occurred
>
> 2: glm.fit: fitted probabilities numerically 0 or 1 occurred
>
> 3: glm.fit: algorithm did not converge
>
> 4: glm.fit: fitted probabilities numerically 0 or 1 occurred
>
>
>
>
>
>
>
> Any help would be greatly appreciated.
>
>
>
> Happy New Year!
>
> David
>
>
>
> ==============================
>
> David Crow
>
> Profesor-Investigador / Assistant Professor
>
> División de Estudios Internacionales
>
> Centro de Investigación y Docencia Económicas
>
>
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>
>
>
> ==============================
>
>
>
>
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>
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David Winsemius, MD
West Hartford, CT