[R] crr - computationally singular

[David Winsemius]

Still the same reasons. It is possible to have collinearity without  
having any one column be a multiple of another.

 > xyz <- data.frame(x=sample(1:1000, 5), y=sample(1:1000, 5) ,  
xx=sample(1:1000, 5) ,yy=sample(1:1000, 5) )
 > xyz$z <- xyz$x + xyz$y + xyz$xx
 > solve(xyz)
Error in solve.default(xyz) :
   system is computationally singular: reciprocal condition number =  
6.39164e-20

On Jun 26, 2009, at 6:22 AM, Laura Bonnett wrote:

> Dear Sir,
>
> Thank you for your response.  You were correct, I had 1 linearly
> dependent column.  I have solved this problem and now the rank of
> 'covaeb' is 17 (qr(covaeb)$rank = 17).  However, I still get the same
> error message when I use covaeb in the 'crr' function.
>
>> fit=crr(snearmb$with.Withtime,csaeb,covaeb,failcode=2,cencode=0)
> 8 cases omitted due to missing values
> Error in drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE =  
> "base")) :
>  system is computationally singular: reciprocal condition number =  
> 3.45905e-25
>
> Are there any other reasons why this may be happening?
>
> Thank you,
>
> Laura
>
> 2009/6/25 Ravi Varadhan <RVaradhan at jhmi.edu>:
>> This means that your design matrix or model matrix is rank  
>> deficient, i.e it
>> does not have linearly independent columns.  Your predictors are  
>> collinear!
>>
>>
>> Just take your design matrices "covaea" or "covaeb" with 17  
>> predcitors and
>> compute their rank or try to invert them.  You will see the problem.
>>
>> Ravi.
>>
>> ----------------------------------------------------------------------------
>> -------
>>
>> Ravi Varadhan, Ph.D.
>>
>> Assistant Professor, The Center on Aging and Health
>>
>> Division of Geriatric Medicine and Gerontology
>>
>> Johns Hopkins University
>>
>> Ph: (410) 502-2619
>>
>> Fax: (410) 614-9625
>>
>> Email: rvaradhan at jhmi.edu
>>
>> Webpage:
>> http://www.jhsph.edu/agingandhealth/People/Faculty_personal_pages/Varadhan.h
>> tml
>>
>>
>>
>> ----------------------------------------------------------------------------
>> --------
>>
>>
>> -----Original Message-----
>> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org 
>> ] On
>> Behalf Of Laura Bonnett
>> Sent: Thursday, June 25, 2009 11:39 AM
>> To: r-help at r-project.org
>> Subject: [R] crr - computationally singular
>>
>> Dear R-help,
>>
>> I'm very sorry to ask 2 questions in a week.  I am using the  
>> package 'crr'
>> and it does exactly what I need it to when I use the dataset a.
>> However, when I use dataset b I get the following error message:
>> Error in drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE =  
>> "base")) :
>>  system is computationally singular: reciprocal condition number =
>> 1.28654e-24
>>
>> This is obviously as a result of a problem with the data but apart  
>> from
>> dataset a having 1674 rows and dataset b having 701 rows there is  
>> really no
>> difference between them.
>>
>> The code I am using is as follows where covaea and covaeb are  
>> matrices of
>> covarites, all coded as binary variables.
>> In case a:
>>> covaea <-
>>> cbind 
>>> (sexa,fsha,fdra,nsigna,eega,th1a,th2a,stype1a,stype2a,stype3a,pgu
>>> 1a,pgu2a,log(agea),firstinta/1000,totsezbasea)
>>> fita <- crr(snearma$with.Withtime,csaea,covaea,failcode=2,cencode=0)
>>
>> and in case b:
>>> covaeb <-
>>> cbind 
>>> (sexb,fshb,fdrb,nsignb,eegb,th1b,th2b,stype1b,stype2b,stype3b,sty
>>> pe4b,stype5b,pgu1b,pgu2b,(ageb/10)^(-1),firstintb,log(totsezbaseb))
>>> fitb <- crr(snearmb$with.Withtime,csaeb,covaeb,failcode=2,cencode=0)
>>
>> csaea and csaeb are the censoring indicators for a and b  
>> respectively which
>> equal 1 for the event of interest, 2 for the competing risks event  
>> and 0
>> otherwise.
>>
>> Can anyone suggest a reason for the error message?  I've tried  
>> running fitb
>> with variants of covaeb and irrespective of the order of the  
>> covariates in
>> the matrix, the code runs fine with 16 of the 17 covariates  
>> included but
>> then produces an error message when the 17th is added.
>>
>> Thank you for your help,
>>
>> Laura
>>
>> ______________________________________________
>> R-help at 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.
>>
>>
>
> ______________________________________________
> R-help at 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
Heritage Laboratories
West Hartford, CT