Running examples in 'RSiena-Ex.R' failed
The error most likely occurred in:

> ### Name: sienaGOF-auxiliary
> ### Title: Auxiliary functions for goodness of fit assessment by 'sienaGOF'
> ### Aliases: sienaGOF-auxiliary sparseMatrixExtraction networkExtraction
> ###   behaviorExtraction OutdegreeDistribution IndegreeDistribution
> ###   BehaviorDistribution TriadCensus mixedTriadCensus
> ### Keywords: models
> 
> ### ** Examples
> 
> ### For use out of the box:
> 
> mynet1 <- sienaDependent(array(c(s501, s502), dim=c(50, 50, 2)))
> mybeh <- sienaDependent(s50a[,1:2], type="behavior")
> mydata <- sienaDataCreate(mynet1, mybeh)
> myeff <- getEffects(mydata)
> myeff <- includeEffects(myeff, transTies, cycle3)
  effectName      include fix   test  initialValue parm
1 3-cycles        TRUE    FALSE FALSE          0   0   
2 transitive ties TRUE    FALSE FALSE          0   0   
> # Shorter phases 2 and 3, just for example:
> myalgorithm <- sienaAlgorithmCreate(nsub=1, n3=50, seed=1234)
> (ans <- siena07(myalgorithm, data=mydata, effects=myeff, returnDeps=TRUE,
+    batch=TRUE))

Start phase 0 
theta:  4.696 -1.489  0.000  0.000  0.000  0.706  0.322  0.000 

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: 1%
Phase 1 Iteration 5 Progress: 1%
Phase 1 Iteration 10 Progress: 1%
Phase 1 Iteration 15 Progress: 2%
Phase 1 Iteration 20 Progress: 3%
Phase 1 Iteration 25 Progress: 3%
Phase 1 Iteration 30 Progress: 4%
Phase 1 Iteration 35 Progress: 5%
Phase 1 Iteration 40 Progress: 5%
Phase 1 Iteration 45 Progress: 6%
Phase 1 Iteration 50 Progress: 7%
theta:  5.0484 -1.6243  0.2850  0.0935  0.1592  0.7005  0.4584 -0.0217 

Start phase 2.1
Phase 2 Subphase 1 Iteration 1 Progress: 61%
Phase 2 Subphase 1 Iteration 2 Progress: 61%
theta  5.2735 -1.7521  0.5377  0.3494  0.3283  0.6697  0.5812 -0.0188 
ac  0.804  0.354  1.359  2.198  2.619  0.276 -2.847 -0.321 
Phase 2 Subphase 1 Iteration 3 Progress: 61%
Phase 2 Subphase 1 Iteration 4 Progress: 62%
theta  5.7924 -2.1199  1.2845  0.5664  0.6006  0.7837  0.7225 -0.0423 
ac  0.434  1.019  1.356  1.834  2.552 -0.151  0.163 -0.820 
Phase 2 Subphase 1 Iteration 5 Progress: 62%
Phase 2 Subphase 1 Iteration 6 Progress: 62%
theta  5.504 -2.363  1.621  0.523  0.770  0.843  0.635 -0.148 
ac  0.4255  1.0094  1.3385  1.3270  1.8105  0.0272  0.1869 -0.7992 
Phase 2 Subphase 1 Iteration 7 Progress: 62%
Phase 2 Subphase 1 Iteration 8 Progress: 62%
theta  5.545 -2.531  1.891  0.273  0.779  0.962  0.556 -0.214 
ac  0.460  1.021  1.360  1.310  1.962  0.279  0.224 -0.113 
Phase 2 Subphase 1 Iteration 9 Progress: 62%
Phase 2 Subphase 1 Iteration 10 Progress: 62%
theta  6.478 -2.641  2.220  0.263  0.807  1.114  0.539 -0.194 
ac  0.5459  1.0150  1.3416  1.2730  1.9759  0.2268  0.3880 -0.0566 
theta  6.8062 -2.6093  1.9810  0.3773  0.7991  1.2040  0.3236 -0.0441 
ac  0.1473 -0.2914 -0.3731 -0.4237 -0.4420 -0.0775 -0.0755  0.0174 
theta:  6.8062 -2.6093  1.9810  0.3773  0.7991  1.2040  0.3236 -0.0441 

Start phase 3 
Estimates, standard errors and convergence t-ratios

                                      Estimate   Standard   Convergence 
                                                   Error      t-ratio   
Network Dynamics 
  1. rate basic rate parameter mynet1  6.8062  ( 8.2697   )   -0.1743   
  2. eval outdegree (density)         -2.6093  ( 2.0049   )   -0.0069   
  3. eval reciprocity                  1.9810  ( 1.8704   )    0.1229   
  4. eval 3-cycles                     0.3773  ( 1.9320   )    0.0167   
  5. eval transitive ties              0.7991  ( 2.9083   )    0.0509   

Behavior Dynamics
  6. rate rate mybeh period 1          1.2040  ( 1.4191   )   -0.3297   
  7. eval mybeh linear shape           0.3236  ( 1.4249   )   -0.1434   
  8. eval mybeh quadratic shape       -0.0441  ( 0.1327   )    0.1040   

Overall maximum convergence ratio:    0.7505 


Total of 337 iteration steps.

> 
> OutdegreeDistribution(NULL, ans$f, ans$sims, period=1, groupName="Data1",
+   levls=0:7, varName="mynet1")
 0  1  2  3  4  5  6  7 
 3 15 27 42 47 50 50 50 
> IndegreeDistribution(5, ans$f, ans$sims, period=1, groupName="Data1",
+   varName="mynet1")
 0  1  2  3  4  5  6  7  8 
 8 19 24 32 38 45 48 49 49 
> BehaviorDistribution(20, ans$f, ans$sims, period=1, groupName="Data1",
+   varName="mybeh")
 1  2  3  4  5 
 4 16 31 40 50 
> sparseMatrixExtraction(50, ans$f, ans$sims, period=1, groupName="Data1",
+   varName="mynet1")
50 x 50 sparse Matrix of class "dgCMatrix"
Error in isFALSE(suppRows) : could not find function "isFALSE"
Calls: <Anonymous> -> <Anonymous> -> printSpMatrix2
Execution halted