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

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: sienaGOF
> ### Title: Functions to assess goodness of fit for SAOMs
> ### Aliases: sienaGOF plot.sienaGOF descriptives.sienaGOF
> ### Keywords: models
> 
> ### ** Examples
> 
> mynet <- sienaDependent(array(c(s501, s502), dim=c(50, 50, 2)))
> mybeh <- sienaDependent(s50a[,1:2], type="behavior")
> mydata <- sienaDataCreate(mynet, mybeh)
> myeff <- getEffects(mydata)
> myeff <- includeEffects(myeff, transTrip)
  effectNumber effectName          shortName include fix   test  initialValue
1 21           transitive triplets transTrip TRUE    FALSE FALSE          0  
  parm
1 0   
> myeff <- setEffect(myeff, cycle3, fix=TRUE, test=TRUE)
  effectNumber effectName shortName include fix  test initialValue parm
1 41           3-cycles   cycle3    TRUE    TRUE TRUE          0   0   
> myeff <- setEffect(myeff, transTies, fix=TRUE, test=TRUE)
  effectNumber effectName      shortName include fix  test initialValue parm
1 44           transitive ties transTies TRUE    TRUE TRUE          0   0   
> myalgorithm <- sienaAlgorithmCreate(nsub=1, n3=10, projname=NULL)
If you use this algorithm object, siena07 will create/use an output file Siena.txt .
> # Shorter phases 2 and 3, just for example.
> ans <- siena07(myalgorithm, data=mydata, effects=myeff, batch=TRUE, returnDeps=TRUE)

Start phase 0 
theta:  4.696 -1.489  0.000  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:  5.696 -1.908  0.514  0.681  0.000  0.000  0.709  0.345 -0.278 

Start phase 2.1
Phase 2 Subphase 1 Iteration 1 Progress: 67%
Phase 2 Subphase 1 Iteration 2 Progress: 67%
theta  6.007 -2.082  0.840  0.957  0.000  0.000  0.749  0.366 -0.313 
ac  0.3023  0.1750 -1.4710 -0.0893 -0.1710 -0.1920  1.4114  0.1309  1.4477 
Phase 2 Subphase 1 Iteration 3 Progress: 67%
Phase 2 Subphase 1 Iteration 4 Progress: 67%
theta  6.090 -2.170  1.301  0.632  0.000  0.000  0.853  0.376 -0.216 
ac  0.3335  0.1784 -0.4113 -0.0879 -0.1534 -0.1850  0.9747  0.3595  1.3460 
Phase 2 Subphase 1 Iteration 5 Progress: 67%
Phase 2 Subphase 1 Iteration 6 Progress: 67%
theta  6.257 -2.258  1.759  0.466  0.000  0.000  0.964  0.411 -0.172 
ac  0.7032  0.0604 -1.4490 -0.4906 -0.8705 -0.7829  0.9337  0.2695  1.1012 
Phase 2 Subphase 1 Iteration 7 Progress: 68%
Phase 2 Subphase 1 Iteration 8 Progress: 68%
theta  6.1419 -2.2625  1.9824  0.2314  0.0000  0.0000  1.0811  0.3898 -0.0324 
ac  0.815 -0.187 -1.663 -0.705 -1.140 -0.957  0.923  0.263  0.828 
Phase 2 Subphase 1 Iteration 9 Progress: 68%
Phase 2 Subphase 1 Iteration 10 Progress: 68%
theta  6.052 -2.270  2.156  0.188  0.000  0.000  1.158  0.379 -0.011 
ac  0.799 -0.234 -1.794 -0.817 -1.283 -0.970  0.887  0.367  0.763 
theta  5.9105 -2.4944  2.2232  0.5312  0.0000  0.0000  1.2043  0.3472 -0.0688 
ac  0.0317 -0.4744 -0.4626 -0.3147 -0.3240 -0.7433  0.1783 -0.1249 -0.1833 
theta:  5.9105 -2.4944  2.2232  0.5312  0.0000  0.0000  1.2043  0.3472 -0.0688 

Start phase 3 
> gofi <- sienaGOF(ans, IndegreeDistribution, verbose=TRUE, join=TRUE,
+   varName="mynet")
Detected 10 iterations and 1 group.
Calculating auxiliary statistics for period  1 .
  Period 1

  > Completed  10  calculations

Estimating test statistic for model including 3-cycles

Estimating test statistic for model including transitive ties

> summary(gofi)
Siena Goodness of Fit ( IndegreeDistribution ), all periods
=====
Monte Carlo Mahalanobis distance test p-value:  0 
**Note: Only 8 statistics are necessary in the auxiliary function.
-----
One tailed test used  (i.e. estimated probability of greater distance than observation).
-----
Calculated joint MHD = ( 15.42 ) for current model.

One-step estimates and predicted Mahalanobis distances for modified models.

**Model including 3-cycles 
                           one-step
basic rate parameter mynet    4.470
outdegree (density)          -2.349
reciprocity                   1.176
transitive triplets           0.720
3-cycles                      0.093
transitive ties               0.000
rate mybeh period 1           1.050
mybeh linear shape            0.532
mybeh quadratic shape        -0.015
MHD                          -7.059

**Model including transitive ties 
                           one-step
basic rate parameter mynet    4.588
outdegree (density)          -2.207
reciprocity                   1.556
transitive triplets           0.491
3-cycles                      0.000
transitive ties               0.692
rate mybeh period 1           1.738
mybeh linear shape            0.823
mybeh quadratic shape        -0.327
MHD                          -4.028

-----
Computation time for auxiliary statistic calculations on simulations:  0.03 seconds.
> plot(gofi)
Note: some statistics are not plotted because their variance is 0.
This holds for the statistic: 8.
> 
> # Illustration just for showing a case with two dependent networks;
> # running time backwards is not meaningful!
> mynet1 <- sienaDependent(array(c(s501, s502), dim=c(50, 50, 2)))
> mynet2 <- sienaDependent(array(c(s503, s501), dim=c(50, 50, 2)))
> mybeh <- sienaDependent(s50a[,1:2], type="behavior")
> mydata <- sienaDataCreate(mynet1, mynet2, mybeh)
> myeff <- getEffects(mydata)
> myeff <- includeEffects(myeff, transTrip)
  effectNumber effectName                  shortName include fix   test 
1 21           mynet1: transitive triplets transTrip TRUE    FALSE FALSE
  initialValue parm
1          0   0   
> myeff <- includeEffects(myeff, recip, name="mynet2")
  effectNumber effectName          shortName include fix   test  initialValue
1 742          mynet2: reciprocity recip     TRUE    FALSE FALSE          0  
  parm
1 0   
> # Shorter phases 2 and 3, just for example.
> ans <- siena07(myalgorithm, data=mydata, effects=myeff, batch=TRUE, returnDeps=TRUE)

Start phase 0 
theta:  4.696 -1.489  0.000  0.000  5.430 -1.542  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: 0%
Phase 1 Iteration 5 Progress: 1%
Phase 1 Iteration 10 Progress: 1%
Phase 1 Iteration 15 Progress: 2%
Phase 1 Iteration 20 Progress: 2%
Phase 1 Iteration 25 Progress: 3%
Phase 1 Iteration 30 Progress: 4%
Phase 1 Iteration 35 Progress: 4%
Phase 1 Iteration 40 Progress: 5%
Phase 1 Iteration 45 Progress: 6%
Phase 1 Iteration 50 Progress: 6%
theta:  4.5590 -1.4493  0.0119 -0.0811  5.4095 -1.6225  0.2732  0.3529  0.9431 -0.1916 

Start phase 2.1
Phase 2 Subphase 1 Iteration 1 Progress: 69%
Phase 2 Subphase 1 Iteration 2 Progress: 69%
theta  3.589 -1.750  0.322  0.998  6.325 -1.393  0.492  1.104  0.215  0.560 
ac  7.7394  0.1583 -3.0087 -0.3496  0.0279  0.1039  2.0494 36.3239  1.5165 -0.1518 
Phase 2 Subphase 1 Iteration 3 Progress: 69%
Phase 2 Subphase 1 Iteration 4 Progress: 69%
theta  2.417 -2.529  0.538  3.400  9.563 -0.174 -0.520  4.385 -3.121  3.792 
ac 6.249 0.502 0.344 0.454 0.573 0.579 1.996 0.726 0.852 0.758 
Phase 2 Subphase 1 Iteration 5 Progress: 69%
Phase 2 Subphase 1 Iteration 6 Progress: 69%
theta  1.908 -3.177  0.547  5.301 12.550  0.969 -1.806  7.645 -6.467  6.991 
ac 1.865 0.609 0.543 0.612 0.721 0.744 1.997 0.876 0.924 0.876 
Phase 2 Subphase 1 Iteration 7 Progress: 69%
Phase 2 Subphase 1 Iteration 8 Progress: 70%
theta  1.687 -3.857  0.523  7.322 15.489  2.073 -3.230 11.014 -9.934 10.316 
ac 1.280 0.664 0.657 0.674 0.810 0.830 1.920 0.916 0.949 0.916 
Phase 2 Subphase 1 Iteration 9 Progress: 70%
Phase 2 Subphase 1 Iteration 10 Progress: 70%
theta   1.552  -4.542   0.561   9.356  18.198   3.061  -4.607  14.270 -13.288  13.543 
ac 1.056 0.685 0.664 0.696 0.870 0.878 1.924 0.937 0.961 0.937 
The update steps have led to a parameter with maximum absolute value 50.09672 ,
which is larger than thetaBound = 50 .
                                           larger
 [1,] basic rate parameter mynet1 1.038          
 [2,] mynet1: outdegree (density) -12.616        
 [3,] mynet1: reciprocity         1.0898         
 [4,] mynet1: transitive triplets 34.7501        
 [5,] basic rate parameter mynet2 45.69          
 [6,] mynet2: outdegree (density) 13.0664        
 [7,] mynet2: reciprocity         -19.6019       
 [8,] rate mybeh period 1         50.0318   *****
 [9,] mybeh linear shape          -50.0967       
[10,] mybeh quadratic shape       49.2195        
Error in doIterations(z, x, subphase, ...) : 
  thetaBound should be set higher.
Calls: siena07 ... robmon -> phase2.1 -> proc2subphase -> doIterations
Execution halted
Examples with CPU (user + system) or elapsed time > 5s
                    user system elapsed
sienaGOF-auxiliary 6.535  0.063   8.486
siena07            5.235  0.032   6.923