[Rsiena-help] What does this error mean?
Victor, Jennifer Nicoll
jnvictor at pitt.edu
Wed Mar 21 21:43:34 CET 2012
Dear Ruth,
Across the three waves 22% of observations appear only in one wave. There is no opportunity for actors to enter between waves. Does this suggest Siena is not a good platform for these data?
My adjcommxxx objects are class matrix. I created them by following the example in the manual, namely:
#111TH COMMITTEES
temp1 <- as(comm111.full, "dgTMatrix")
edges111 <- cbind(temp1 at i+1, temp1 at j+1, temp1 at x)
#CREATE EMPTY ADJACENCY MATRIX
adjcomm111 <- matrix(0, 555, 555)
#PUT EDGE VALUES IN DESIRED PLACES
adjcomm111[edges111[, 1:2]] <- edges111[,3]
#CHECK LENGTH
length(which(comm111.full !=adjcomm111))
#THIS RETURNS 0, WHICH IS CORRECT
Best,
Jennifer
___________________________________________
Jennifer Nicoll Victor
Assistant Professor
Department of Political Science
University of Pittsburgh
4600 Wesley W. Posvar Hall
(412) 624-7204
E-mail: jnvictor at pitt.edu
Homepage: http://www.polisci.pitt.edu/person/jennifer-nicoll-victor
-----Original Message-----
From: Ruth Ripley [mailto:ruth at stats.ox.ac.uk]
Sent: Wednesday, March 21, 2012 4:29 PM
To: Victor, Jennifer Nicoll
Cc: rsiena-help at r-forge.wu-wien.ac.at
Subject: Re: [Rsiena-help] What does this error mean?
Dear Jennifer,
10's will work correctly in RSiena, but they will not work in sna.
There is little point having actors who are only present at time 3. If
you assume they arrive at time 2.5 they could be used in the simulation.
Similarly you might want to assume that actor 3 leaves at some time
after 2.0.
What format are your adjcommxxx? Try class(adjcommxxx) to find out. They
should be dgTMatrix.
Regards,
Ruth
On 21/03/2012 20:14, Victor, Jennifer Nicoll wrote:
> Thanks, Ruth. As indicated in the manual, I have the structural zeroes in RSiena data set to "10," rather than "NA." This is correct, yes?
>
> Could my trouble have to do with the exogenous events file? I specified this file as the manual instructed and then used the command:
> compChange.us<-sienaCompositionChange(usexevents)
>
> Where my "usexevents" file looks like this:
> V2 V3
> 1 1 3
> 2 1 3
> 3 1 2
> 4 3 3
>
> (for the first four actors, where actors 1& 2 are present in all three time periods, and actor 2 is present only in the first two time periods, and actor 4 is present only in the 3 time period).
>
> I received no errors with my sienaCompositionChange command, but I wonder if there is a problem?
>
> As an aside, I also have trouble with the command:
> uscom<-varDyadCovar(list(adjcomm110, adjcomm111))
> Error in varDyadCovar(list(adjcomm110, adjcomm111)) :
> not a list of sparse triples matrices
>
> My "adjcommxxx" files are sparse matrices, but I'm not certain about the "triples" part.
>
> JNV
> ___________________________________________
> Jennifer Nicoll Victor
> Assistant Professor
> Department of Political Science
> University of Pittsburgh
> 4600 Wesley W. Posvar Hall
> (412) 624-7204
> E-mail: jnvictor at pitt.edu
> Homepage: http://www.polisci.pitt.edu/person/jennifer-nicoll-victor
>
>
> -----Original Message-----
> From: Ruth Ripley [mailto:ruth at stats.ox.ac.uk]
> Sent: Wednesday, March 21, 2012 3:14 PM
> To: Victor, Jennifer Nicoll
> Cc: rsiena-help at r-forge.wu-wien.ac.at
> Subject: Re: [Rsiena-help] What does this error mean?
>
> Dear Jennifer,
>
> The error you have indicates that the simulation process is failing.
> Either steps are happening so frequently that the cumulative time is
> increasing too slowly, or, more likely here, in conditional estimation,
> every step is choosing to do nothing so the target cannot be reached.
>
> One point about sna: having seen some of your data, I wonder if you had
> any structural zeros in the matrix you used with sna. sna does not
> recognise these.
>
> Regards,
>
> Ruth
>
> On 21/03/2012 15:38, Victor, Jennifer Nicoll wrote:
>> Thank you to Ruth Ripley and Nate Doogan for providing help with
>> this
> modeling problem. Based on their suggestions I have simplified the model
> and the effects; however, I still am unable to estimate the model. I'm
> seeking some general advice about fitting my data. Ruth wondered if
> Siena was the appropriate model for these data and I'm attempting to
> investigate this question and get more feedback. I appreciate further
> feedback from users of this list. I've also posted to the general
> Statnet list and have estimated ERGMs with these data.
>>
>> I have encountered numerous problems relating to degeneracy and
>> model
> specification. The data are from three waves (congresses) of US members
> of Congress and their co-membership in legislative organizations. I have
> a number of dyadic and nodal attribute variables as well about the
> actors. The hypothesis I seek to test is whether there are bridging-ties
> among the legislators through their memberships in legislative
> organizations. I suspect that the high degree of density in the data may
> be part of the problem.
>>
>> One approach I've tried is to simply calculate betweenness (in the
>> SNA
> package) for each network of legislators in each time period, add this
> as a vertex attribute, and estimate an ERGM, in which betweenness is a
> nodal-covariate; however these models have difficulty with convergence
> and fit. I am unable to obtain MCMC standard errors, and even after
> numerous attempts at respecification the diagnostics suggest that fit
> may be problematic.
>>
>> Another approach is to use Siena. Siena should allow me to take
> advantage of the longitudinal nature of the data. But the output that
> I've been able to obtain suggests that the model is problematic, as Ruth
> and Nate have pointed out. See output below.
>>
>> So my various attempts at testing this hypothesis using these
>> advanced
> methods have left me frustrated. While we can (and have) tested the idea
> using a variety of less sophisticated methods, it seems to me that the
> advanced statistical methods, such as those available through ERGM and
> Siena, are designed for exactly this type of modeling; however, I have
> not been able to achieve satisfactory findings that are reportable. I
> can continue to try to reparameterize the models to search for fit and
> to avoid degeneracy, but I would like to hear thoughts of readers of
> this list regarding:
>> - the appropriate method for testing the hypothesis - best practices
>> for iterative modeling and specification for these
> types of models (given that each iteration is so computationally expensive)
>> - which architecture (ERGM, Siena, something else?) seems most
> appropriate for the data?
>>
>> Siena verbose output:
>>> myeffus
>> effectName include fix test initialValue parm
>> 1 constant caucuses rate (period 1) TRUE FALSE FALSE 100.00000 0
>> 2 constant caucuses rate (period 2) TRUE FALSE FALSE 70.41182 0
>> 3 degree (density) TRUE FALSE FALSE 0.03424 0
>> 4 betweenness TRUE FALSE FALSE 0.00000 0
>> 5 same usparty TRUE FALSE FALSE 0.00000 0
>>> myusmodel<-sienaModelCreate(useStdInits=FALSE, projname='siena_us_02')
>>> usans02<-siena07(myusmodel, data=myusdata,effects=myeffus, batch=TRUE, verbose=TRUE)
>>
>> Stochastic approximation algorithm.
>> Initial value for gain parameter = 0.2.
>> Start of the algorithm.
>> Observed function values are
>> 1. 123349.0000 2. 5156392.0000 3. 123580.0000
>>
>> Start phase 0
>> theta: 0.0342 0.0000 0.0000
>> Current parameter values:
>> 0.03424475 0.00000000 0.00000000
>>
>> Start phase 1
>> Phase 1 Iteration 1 Progress: 0%
>> Phase 1 Iteration 2 Progress: 0%
>> Phase 1 Iteration 3 Progress: 0%
>> Phase 1 Iteration 4 Progress: 0%
>> Phase 1 Iteration 5 Progress: 0%
>> Phase 1 Iteration 10 Progress: 0%
>> Phase 1 Iteration 15 Progress: 1%
>> Time per iteration in phase 1 = 50.7582
>> Average deviations NR generated statistics and targets
>> after phase 1:
>> -39637.750000
>> 6787139.500000
>> -39249.250000
>>
>> Diagonal values of derivative matrix :
>> 32772.3901 524963179.7438 38364.4002
>> dfra :
>> 32772.39 3087677.74 17924.11
>> 5095442.50 524963179.74 3357687.99
>> 39393.49 3556965.56 38364.40
>>
>> inverse of dfra :
>> 0.00029660366044 -0.00000197940840 0.00003466438151
>> -0.00000228738847 0.00000001994553 -0.00000067696765
>> -0.00009248392723 0.00000018324891 0.00005323684804
>>
>> Full Quasi-Newton-Raphson step after phase 1:
>> 1. 26.551774
>> 2. -0.252611
>> 3. -2.820084
>> This step is multiplied by the factor 0.10000.
>> Intervention 1.4.2: jump after phase 1 decreased by factor 26.5517736817607 .
>> Phase 1 achieved after 16 iterations.
>> theta: 1.03424 -0.00951 -0.10621
>> Current parameter values:
>> 1.034244749 -0.009513884 -0.106210769
>>
>> Phase 2 has 4 subphases.
>> Each subphase can be repeated up to 4 times
>>
>> Start phase 2.1
>> Phase 2 Subphase 1 Iteration 1 Progress: 3%
>> Phase 2 Subphase 1 Iteration 2 Progress: 3%
>> theta 1.0433 -0.0096 -0.0982
>> ac 1.009 0.985 1.014
>> Phase 2 Subphase 1 Iteration 3 Progress: 3%
>> Phase 2 Subphase 1 Iteration 4 Progress: 3%
>> theta 1.06134 -0.00977 -0.08233
>> ac 1.006 0.992 1.008
>> Phase 2 Subphase 1 Iteration 5 Progress: 3%
>> Phase 2 Subphase 1 Iteration 6 Progress: 3%
>> theta 1.07940 -0.00994 -0.06651
>> ac 1.01 0.99 1.01
>> Phase 2 Subphase 1 Iteration 7 Progress: 3%
>> Phase 2 Subphase 1 Iteration 8 Progress: 3%
>> theta 1.0975 -0.0101 -0.0508
>> ac 1.004 0.995 1.007
>> Phase 2 Subphase 1 Iteration 9 Progress: 3%
>> Phase 2 Subphase 1 Iteration 10 Progress: 3%
>> theta 1.1155 -0.0103 -0.0353
>> ac 1.004 0.996 1.006
>> Phase 2 Subphase 1 Iteration 20 Progress: 3%
>> theta 1.2058 -0.0112 0.0411
>> ac 1.002 0.999 1.006
>> Phase 2 Subphase 1 Iteration 30 Progress: 4%
>> theta 1.2961 -0.0121 0.1146
>> ac 1.00 1.00 1.01
>> Phase 2 Subphase 1 Iteration 40 Progress: 4%
>> theta 1.386 -0.013 0.185
>> ac 1.00 1.00 1.01
>> Phase 2 Subphase 1 Iteration 50 Progress: 5%
>> theta 1.4767 -0.0139 0.2526
>> ac 1.00 1.00 1.01
>> Phase 2 Subphase 1 Iteration 60 Progress: 5%
>> theta 1.5670 -0.0148 0.3167
>> ac 1.00 1.00 1.01
>> Phase 2 Subphase 1 Iteration 70 Progress: 5%
>> theta 1.6574 -0.0157 0.3777
>> ac 1.00 1.00 1.01
>> Phase 2 Subphase 1 Iteration 80 Progress: 6%
>> theta 1.7477 -0.0166 0.4350
>> ac 1.00 1.00 1.01
>> Phase 2 Subphase 1 Iteration 90 Progress: 6%
>> theta 1.8380 -0.0174 0.4888
>> ac 1.00 1.00 1.01
>> Phase 2 Subphase 1 Iteration 100 Progress: 7%
>> theta 1.9283 -0.0182 0.5386
>> ac 1.00 1.00 1.01
>> Phase 2 Subphase 1 Iteration 110 Progress: 7%
>> theta 2.019 -0.019 0.585
>> ac 1.00 1.00 1.01
>> Error in x$FRAN(zsmall, xsmall) :
>> Unlikely to terminate this epoch: more than 1000000 steps
>> Calls: siena07 ... proc2subphase -> doIterations -> <Anonymous> -> .Call
>> Execution halted
>>
>>
>> If you got to the end of this post, I appreciate your attention and any advice you might have!
>> Best,
>> Jennifer Victor
>> ___________________________________________
>> Jennifer Nicoll Victor
>> Assistant Professor
>> Department of Political Science
>> University of Pittsburgh
>> 4600 Wesley W. Posvar Hall
>> (412) 624-7204
>> E-mail: jnvictor at pitt.edu
>> Homepage: http://www.polisci.pitt.edu/person/jennifer-nicoll-victor
>>
>>
>> -----Original Message-----
>> From: rsiena-help-bounces at r-forge.wu-wien.ac.at [mailto:rsiena-help-bounces at r-forge.wu-wien.ac.at] On Behalf Of Ruth Ripley
>> Sent: Friday, March 09, 2012 8:39 AM
>> To: rsiena-help at r-forge.wu-wien.ac.at
>> Subject: Re: [Rsiena-help] What does this error mean?
>>
>> Dear Jennifer,
>>
>> The errors both indicate that you are fitting a model which is too
>> complicated for your data. I suggest you start with just the default
>> effects and add others one by one to see which one is giving the problem.
>>
>> Regards,
>>
>> Ruth
>>
>> On 09/03/2012 02:45, Victor, Jennifer Nicoll wrote:
>>> After letting my RSiena model for 12 hours on a high memory machine I received the following output. What advice can you provide to help me overcome this error?
>>>
>>>> myusmodel<-sienaModelCreate(useStdInits=FALSE, projname='siena_us_01')
>>>> usans01<-siena07(myusmodel, data=myusdata,effects=myeffus)
>>> No X11 device available, forcing use of batch mode
>>> Start phase 0
>>> theta: 0.0342 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
>>>
>>> Start phase 1
>>> Phase 1 Iteration 1 Progress: 0%
>>> Phase 1 Iteration 2 Progress: 0%
>>> Phase 1 Iteration 3 Progress: 0%
>>> Phase 1 Iteration 4 Progress: 0%
>>> Phase 1 Iteration 5 Progress: 0%
>>> Phase 1 Iteration 10 Progress: 0%
>>> Phase 1 Iteration 15 Progress: 0%
>>> Phase 1 Iteration 20 Progress: 1%
>>> Phase 1 Iteration 25 Progress: 1%
>>> Phase 1 Iteration 30 Progress: 1%
>>> Phase 1 Iteration 35 Progress: 1%
>>> Phase 1 Iteration 40 Progress: 1%
>>> Error in solve.default(z$dfra) :
>>> system is computationally singular: reciprocal condition number = 4.58224e-20
>>> theta: 0.03416 0.01123 -0.01203 -0.00364 -0.17691 -0.40977 0.23908 -0.14365 0.25761 1.00000 0.21070
>>>
>>> Start phase 2.1
>>> Phase 2 Subphase 1 Iteration 1 Progress: 14%
>>> Phase 2 Subphase 1 Iteration 2 Progress: 14%
>>> theta 0.04034 0.01130 -0.01206 -0.00342 -0.17012 -0.40569 0.24425 -0.13712 0.25683 0.99919 0.20914
>>> ac 1.063 1.049 1.006 1.044 1.025 1.063 1.067 1.065 0.651 0.954 0.866
>>> Phase 2 Subphase 1 Iteration 3 Progress: 14%
>>> Phase 2 Subphase 1 Iteration 4 Progress: 14%
>>> theta 0.05223 0.01144 -0.01213 -0.00299 -0.15670 -0.39786 0.25405 -0.12452 0.25377 0.99722 0.20489
>>> ac 1.136 1.112 1.013 1.096 1.105 1.134 1.161 1.137 0.690 0.984 0.881
>>> Phase 2 Subphase 1 Iteration 5 Progress: 14%
>>> Phase 2 Subphase 1 Iteration 6 Progress: 14%
>>> theta 0.06332 0.01158 -0.01221 -0.00256 -0.14449 -0.39056 0.26230 -0.11261 0.24601 0.99419 0.19779
>>> ac 1.137 1.140 0.936 1.145 1.104 1.136 1.164 1.140 0.863 0.962 0.967
>>> Phase 2 Subphase 1 Iteration 7 Progress: 14%
>>> Error in x$FRAN(zsmall, xsmall) :
>>> Unlikely to terminate this epoch: more than 1000000 steps
>>> Calls: siena07 ... proc2subphase -> doIterations -> <Anonymous> -> .Call
>>> Execution halted
>>>
>>>
>>>
>>> Jennifer N. Victor
>>> Assistant Professor of Political Science
>>> University of Pittsburgh
>>> 4600 Posvar Hall
>>> jnvictor at pitt.edu
>>> (412) 624-7204
>>> _______________________________________________
>>> Rsiena-help mailing list
>>> Rsiena-help at lists.r-forge.r-project.org
>>> https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rsiena-help
>>
>>
>> _______________________________________________
>> Rsiena-help mailing list
>> Rsiena-help at lists.r-forge.r-project.org
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>
>
>
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