[R] error: optim(rho, n2ll.rho, method = method, control = control, beta = parm$beta, : initial value in 'vmmin' is not finite

spencerg spencer.graves at prodsyse.com
Mon Jul 13 02:16:09 CEST 2009


      I have not used 'sna'. 


      Have you tried using "debug" to walk through the code line by 
line, examining and even changing things at will? 


      For example, how big is "rho", passed as starting values to 
"optim"?  If that matches the size of your adjacency matrix, it could 
expose a theoretical problem.  Similarly, how many observations do you 
have?  For example, if you have 2,000 observations, that might help 
explain why you get an answer with adjacency matrices smaller than that 
but not with larger matrices. 


      Hope this helps. 
      Spencer Graves
p.s.  Are you aware that you can get the source code for any CRAN 
package?  For example, the source for the "sna" package is available in 
a file "sna_2.0-1.tar.gz" downloadable from 
"http://cran.fhcrc.org/web/packages/sna/index.html".  If the people who 
wrote a particular functions included comments in their code, they will 
appear in the *.tar.gz file but not in the version you get by typing the 
function name.


Brandy Lee Aven wrote:
> I am trying to use the lnam autocorrelation model from the SNA package. I have it running for smaller adjacency matrices (<1,500) it works just fine but when my matrices are bigger 4000+. I get the error: 
>
>   
>> lnam1_01.adj<- lnam(data01$adopt,x01,ec2001.csr)
>>     
> Error in optim(rho, n2ll.rho, method = method, control = control, beta = parm$beta,  : 
>   initial value in 'vmmin' is not finite
>
>
> I have looked at the lnam code and cant even figure out what vmmin is. 
> Is there anyway around this? Am I doing something wrong? What makes me think that its about the size of the adjacency matrix is that I can run the same command on similar objects that are just smaller and it works fine. 
>
> please help!
>
>   
>> sessionInfo()
>>     
> R version 2.9.1 (2009-06-26) 
> x86_64-pc-linux-gnu 
>
> locale:
> C
>
> attached base packages:
> [1] stats     graphics  grDevices utils     datasets  methods   base     
>
> other attached packages:
> [1] numDeriv_2009.2-1 sna_2.0-1        
>
> loaded via a namespace (and not attached):
> [1] tools_2.9.1
>
>   
>> class(data01$adopt) #This is the response vector y
>>     
> [1] "integer"
>
>   
>> data01$adopt[1:10] # Its just a binary outcome for all vertices
>>     
> [1] 0 0 0 0 0 0 0 0 0 0 ......until 4,003
>
>   
>> class(x01) #X01 is a matrix of my six covariates for all vertices                                      
>>     
> [1] "matrix"
>
> #here is the an example of the data
>   
>> x01[1:10,1:6]
>>     
> 	on01 indegree outdegree	between eigen numalters01
> 1	1	0	0	0	1	1
> 19	1	0	1	0	0	1
> 123	1	0	1	0	0	1
> 140	1	0	1	0	0	1
> 169	1	0	1	0	0	1
> 189	1	0	1	0	0	1
> 195	1	0	1	0	0	2
> 204	1	0	1	0	0	1
> 231	1	0	2	0	0	1
> 252	1	0	3	0	0	4
>
> # this is the adjacency matrix (in Sparse matrix format) that causes the error. I have another that is 10,500 and does the same thing.
>   
>> dim(ec2001.csr) 
>>     
> [1] 4003 4003
>
>   
>> class(ec2001.csr)
>>     
> [1] "matrix.csr"
> attr(,"package")
> [1] "SparseM"
>
>   
>> ec2001.csr[1:10,1:10] #here is what it looks like
>>     
>     1 19 123 140 169 189 195 204 231 252
> 1   1  0   0   0   0   0   0   0   0   0
> 19  0  0   0   1   0   0   0   0   0   0
> 123 0  0   0   0   0   0   0   0   0   0
> 140 0  0   0   0   0   0   0   0   0   0
> 169 0  0   0   0   0   0   0   0   0   0
> 189 0  0   1   0   0   0   0   0   0   0
> 195 0  0   0   0   0   0   0   0   0   0
> 204 0  0   0   0   0   0   0   0   0   0
> 231 0  0   0   0   0   0   0   0   0   0
> 252 0  0   0   0   0   0   0   0   0   0
>
>
> #There are also no infinite values in the objects. 
>   
>> is.infinite(x01)
>>     
> [1] FALSE ..... N
>
>   
>> is.infinite(data01$adopt)
>>     
> [1] FALSE .....N
>
>   
>> is.infinite(ec2001.csr)
>>     
> [1] FALSE
>
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