Error(s) in re-building vignettes:
--- re-building 'valued.Rmd' using rmarkdown
Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-1'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Loading required package: ergm
Loading required package: network

'network' 1.17.1 (2021-06-12), part of the Statnet Project
* 'news(package="network")' for changes since last version
* 'citation("network")' for citation information
* 'https://statnet.org' for help, support, and other information


'ergm' 4.2.1 (2022-05-10), part of the Statnet Project
* 'news(package="ergm")' for changes since last version
* 'citation("ergm")' for citation information
* 'https://statnet.org' for help, support, and other information

'ergm' 4 is a major update that introduces some backwards-incompatible
changes. Please type 'news(package="ergm")' for a list of major
changes.


'ergm.count' 4.0.2 (2021-06-18), part of the Statnet Project
* 'news(package="ergm.count")' for changes since last version
* 'citation("ergm.count")' for citation information
* 'https://statnet.org' for help, support, and other information

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-2'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-3'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-4'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-5'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-6'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-7'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-8'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-9'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Best valid proposal 'DiscUnif' cannot take into account hint(s) 'sparse'.
Best valid proposal 'DiscUnif' cannot take into account hint(s) 'sparse'.
Best valid proposal 'DiscUnif' cannot take into account hint(s) 'sparse'.
Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-10'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Best valid proposal 'Binomial' cannot take into account hint(s) 'sparse'.
Best valid proposal 'Binomial' cannot take into account hint(s) 'sparse'.
Best valid proposal 'Binomial' cannot take into account hint(s) 'sparse'.
Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-11'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Best valid proposal 'Geometric' cannot take into account hint(s) 'sparse'.
Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-12'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-13'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Best valid proposal 'Geometric' cannot take into account hint(s) 'sparse'.
Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-14'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-15'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Best valid proposal 'Binomial' cannot take into account hint(s) 'sparse'.
Starting contrastive divergence estimation via CD-MCMLE:
Iteration 1 of at most 60:
Convergence test P-value:5e-302
The log-likelihood improved by 2.364.
Iteration 2 of at most 60:
Convergence test P-value:9.8e-108
The log-likelihood improved by 0.6556.
Iteration 3 of at most 60:
Convergence test P-value:2.7e-16
The log-likelihood improved by 0.06694.
Iteration 4 of at most 60:
Convergence test P-value:8.1e-08
The log-likelihood improved by 0.03328.
Iteration 5 of at most 60:
Convergence test P-value:1.4e-04
The log-likelihood improved by 0.01995.
Iteration 6 of at most 60:
Convergence test P-value:2.7e-01
The log-likelihood improved by 0.005044.
Iteration 7 of at most 60:
Convergence test P-value:2.1e-03
The log-likelihood improved by 0.01576.
Iteration 8 of at most 60:
Convergence test P-value:4.7e-01
The log-likelihood improved by 0.003545.
Iteration 9 of at most 60:
Convergence test P-value:4.9e-01
The log-likelihood improved by 0.003488.
Iteration 10 of at most 60:
Convergence test P-value:2.5e-02
The log-likelihood improved by 0.01035.
Iteration 11 of at most 60:
Convergence test P-value:2.2e-02
The log-likelihood improved by 0.01068.
Iteration 12 of at most 60:
Convergence test P-value:1.2e-01
The log-likelihood improved by 0.006782.
Iteration 13 of at most 60:
Convergence test P-value:2.6e-01
The log-likelihood improved by 0.005157.
Iteration 14 of at most 60:
Convergence test P-value:5.3e-01
Convergence detected. Stopping.
The log-likelihood improved by 0.003408.
Finished CD.
Starting Monte Carlo maximum likelihood estimation (MCMLE):
Iteration 1 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.9985.
Estimating equations are not within tolerance region.
Iteration 2 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.0589.
Convergence test p-value: 0.3011. Not converged with 99% confidence; increasing sample size.
Iteration 3 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.0259.
Convergence test p-value: 0.0574. Not converged with 99% confidence; increasing sample size.
Iteration 4 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.0312.
Convergence test p-value: 0.0003. Converged with 99% confidence.
Finished MCMLE.
Evaluating log-likelihood at the estimate. Setting up bridge sampling...
Best valid proposal 'Binomial' cannot take into account hint(s) 'sparse'.
Using 16 bridges: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 .
Note: Null model likelihood calculation is not implemented for valued
ERGMs at this time.  This means that all likelihood-based inference
(LRT, Analysis of Deviance, AIC, BIC, etc.) is only valid between
models with the same reference distribution and constraints.
This model was fit using MCMC.  To examine model diagnostics and check
for degeneracy, use the mcmc.diagnostics() function.
Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-16'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-17'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-18'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Starting contrastive divergence estimation via CD-MCMLE:
Iteration 1 of at most 60:
Convergence test P-value:2.2e-102
The log-likelihood improved by 1.967.
Iteration 2 of at most 60:
Convergence test P-value:8e-23
The log-likelihood improved by 0.2124.
Iteration 3 of at most 60:
Convergence test P-value:3.1e-17
The log-likelihood improved by 0.1477.
Iteration 4 of at most 60:
Convergence test P-value:5.1e-15
The log-likelihood improved by 0.1332.
Iteration 5 of at most 60:
Convergence test P-value:2.2e-08
The log-likelihood improved by 0.06473.
Iteration 6 of at most 60:
Convergence test P-value:2e-05
The log-likelihood improved by 0.04161.
Iteration 7 of at most 60:
Convergence test P-value:6.6e-04
The log-likelihood improved by 0.02872.
Iteration 8 of at most 60:
Convergence test P-value:1.4e-02
The log-likelihood improved by 0.01668.
Iteration 9 of at most 60:
Convergence test P-value:1.5e-02
The log-likelihood improved by 0.01619.
Iteration 10 of at most 60:
Convergence test P-value:7.8e-01
Convergence detected. Stopping.
The log-likelihood improved by 0.0009566.
Finished CD.
Starting Monte Carlo maximum likelihood estimation (MCMLE):
Iteration 1 of at most 60:
Optimizing with step length 0.6651.
The log-likelihood improved by 3.2986.
Estimating equations are not within tolerance region.
Iteration 2 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.6919.
Estimating equations are not within tolerance region.
Iteration 3 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.0416.
Convergence test p-value: 0.0055. Converged with 99% confidence.
Finished MCMLE.
Evaluating log-likelihood at the estimate. Setting up bridge sampling...
Using 16 bridges: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 .
Note: Null model likelihood calculation is not implemented for valued
ERGMs at this time.  This means that all likelihood-based inference
(LRT, Analysis of Deviance, AIC, BIC, etc.) is only valid between
models with the same reference distribution and constraints.
This model was fit using MCMC.  To examine model diagnostics and check
for degeneracy, use the mcmc.diagnostics() function.
Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-19'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-20'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Best valid proposal 'Binomial' cannot take into account hint(s) 'sparse'.
Starting contrastive divergence estimation via CD-MCMLE:
Iteration 1 of at most 60:
Convergence test P-value:0e+00
The log-likelihood improved by 2.065.
Iteration 2 of at most 60:
Convergence test P-value:3.4e-224
The log-likelihood improved by 1.517.
Iteration 3 of at most 60:
Convergence test P-value:2.3e-35
The log-likelihood improved by 0.1333.
Iteration 4 of at most 60:
Convergence test P-value:1.6e-13
The log-likelihood improved by 0.05065.
Iteration 5 of at most 60:
Convergence test P-value:2.3e-02
The log-likelihood improved by 0.009607.
Iteration 6 of at most 60:
Convergence test P-value:1.3e-01
The log-likelihood improved by 0.006562.
Iteration 7 of at most 60:
Convergence test P-value:1.7e-01
The log-likelihood improved by 0.006146.
Iteration 8 of at most 60:
Convergence test P-value:6.2e-01
Convergence detected. Stopping.
The log-likelihood improved by 0.002909.
Finished CD.
Starting Monte Carlo maximum likelihood estimation (MCMLE):
Iteration 1 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 1.4104.
Estimating equations are not within tolerance region.
Iteration 2 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.1439.
Estimating equations are not within tolerance region.
Iteration 3 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.3215.
Estimating equations are not within tolerance region.
Iteration 4 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.1246.
Estimating equations are not within tolerance region.
Iteration 5 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.0481.
Convergence test p-value: 0.7945. Not converged with 99% confidence; increasing sample size.
Iteration 6 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.0234.
Convergence test p-value: 0.2837. Not converged with 99% confidence; increasing sample size.
Iteration 7 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.0369.
Convergence test p-value: 0.0422. Not converged with 99% confidence; increasing sample size.
Iteration 8 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.0123.
Convergence test p-value: 0.0011. Converged with 99% confidence.
Finished MCMLE.
Evaluating log-likelihood at the estimate. Setting up bridge sampling...
Best valid proposal 'Binomial' cannot take into account hint(s) 'sparse'.
Using 16 bridges: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 .
Note: Null model likelihood calculation is not implemented for valued
ERGMs at this time.  This means that all likelihood-based inference
(LRT, Analysis of Deviance, AIC, BIC, etc.) is only valid between
models with the same reference distribution and constraints.
This model was fit using MCMC.  To examine model diagnostics and check
for degeneracy, use the mcmc.diagnostics() function.
Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-21'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-22'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Best valid proposal 'Binomial' cannot take into account hint(s) 'sparse'.
Starting contrastive divergence estimation via CD-MCMLE:
Iteration 1 of at most 60:
Convergence test P-value:0e+00
The log-likelihood improved by 1.776.
Iteration 2 of at most 60:
Convergence test P-value:1.1e-164
The log-likelihood improved by 1.22.
Iteration 3 of at most 60:
Convergence test P-value:6.4e-31
The log-likelihood improved by 0.139.
Iteration 4 of at most 60:
Convergence test P-value:7.8e-03
The log-likelihood improved by 0.01254.
Iteration 5 of at most 60:
Convergence test P-value:3.5e-08
The log-likelihood improved by 0.03576.
Iteration 6 of at most 60:
Convergence test P-value:2.3e-01
The log-likelihood improved by 0.005356.
Iteration 7 of at most 60:
Convergence test P-value:1.1e-01
The log-likelihood improved by 0.007178.
Iteration 8 of at most 60:
Convergence test P-value:1.8e-01
The log-likelihood improved by 0.006093.
Iteration 9 of at most 60:
Convergence test P-value:3.8e-02
The log-likelihood improved by 0.009378.
Iteration 10 of at most 60:
Convergence test P-value:8.7e-01
Convergence detected. Stopping.
The log-likelihood improved by 0.001462.
Finished CD.
Starting Monte Carlo maximum likelihood estimation (MCMLE):
Iteration 1 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 2.2755.
Estimating equations are not within tolerance region.
Iteration 2 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.2197.
Estimating equations are not within tolerance region.
Iteration 3 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.0562.
Convergence test p-value: 0.9295. Not converged with 99% confidence; increasing sample size.
Iteration 4 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.1169.
Estimating equations are not within tolerance region.
Iteration 5 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.0118.
Convergence test p-value: 0.0233. Not converged with 99% confidence; increasing sample size.
Iteration 6 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.0194.
Convergence test p-value: 0.4956. Not converged with 99% confidence; increasing sample size.
Iteration 7 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.0143.
Convergence test p-value: 0.0235. Not converged with 99% confidence; increasing sample size.
Iteration 8 of at most 60:
Optimizing with step length 1.0000.
The log-likelihood improved by 0.0111.
Convergence test p-value: 0.0002. Converged with 99% confidence.
Finished MCMLE.
Evaluating log-likelihood at the estimate. Setting up bridge sampling...
Best valid proposal 'Binomial' cannot take into account hint(s) 'sparse'.
Using 16 bridges: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 .
Note: Null model likelihood calculation is not implemented for valued
ERGMs at this time.  This means that all likelihood-based inference
(LRT, Analysis of Deviance, AIC, BIC, etc.) is only valid between
models with the same reference distribution and constraints.
This model was fit using MCMC.  To examine model diagnostics and check
for degeneracy, use the mcmc.diagnostics() function.
Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-23'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-24'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-25'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Evaluating network in model.
Initializing unconstrained Metropolis-Hastings proposal: 'ergm.count:MH_PoissonTNT'.
Initializing model...
Model initialized.
Using initial method 'CD'.
Fitting initial model.
Starting contrastive divergence estimation via CD-MCMLE:
Iteration 1 of at most 60:
Convergence test P-value:0e+00
The log-likelihood improved by 1.58.
Iteration 2 of at most 60:
Convergence test P-value:0e+00
The log-likelihood improved by 1.662.
Iteration 3 of at most 60:
Convergence test P-value:3.5e-125
The log-likelihood improved by 0.4622.
Iteration 4 of at most 60:
Convergence test P-value:6.2e-16
The log-likelihood improved by 0.04696.
Iteration 5 of at most 60:
Convergence test P-value:6e-02
The log-likelihood improved by 0.007382.
Iteration 6 of at most 60:
Convergence test P-value:1.3e-01
The log-likelihood improved by 0.00626.
Iteration 7 of at most 60:
Convergence test P-value:1.6e-02
The log-likelihood improved by 0.009329.
Iteration 8 of at most 60:
Convergence test P-value:2.7e-01
The log-likelihood improved by 0.004911.
Iteration 9 of at most 60:
Convergence test P-value:1.3e-02
The log-likelihood improved by 0.009616.
Iteration 10 of at most 60:
Convergence test P-value:3.3e-01
The log-likelihood improved by 0.00451.
Iteration 11 of at most 60:
Convergence test P-value:7.4e-01
Convergence detected. Stopping.
The log-likelihood improved by 0.002534.
Finished CD.
Starting Monte Carlo maximum likelihood estimation (MCMLE):
Density guard set to 10000 from an initial count of 78 edges.

Iteration 1 of at most 50 with parameter:
                       sum                    nonzero 
                1.17424988                -4.60211481 
nodefactor.sum.leader.TRUE   absdiff.sum.faction.id.1 
               -0.14365247                 0.08161279 
  absdiff.sum.faction.id.2   absdiff.sum.faction.id.3 
               -0.25729197                -1.05030091 
  absdiff.sum.faction.id.4                  nodecovar 
               -1.08211413                 3.22619710 
Starting unconstrained MCMC...
Back from unconstrained MCMC.
New interval = 512.
Average estimating function values:
                       sum                    nonzero 
                892.966245                  77.759494 
nodefactor.sum.leader.TRUE   absdiff.sum.faction.id.1 
                -34.105485                 502.329114 
  absdiff.sum.faction.id.2   absdiff.sum.faction.id.3 
                277.426160                 137.383966 
  absdiff.sum.faction.id.4                  nodecovar 
                 -9.780591                 342.686485 
Starting MCMLE Optimization...
Optimizing with step length 0.0406.
Using lognormal metric (see control.ergm function).
Using log-normal approx (no optim)
The log-likelihood improved by 3.3915.
Estimating equations are not within tolerance region.

Iteration 2 of at most 50 with parameter:
                       sum                    nonzero 
               1.377007487               -5.804802827 
nodefactor.sum.leader.TRUE   absdiff.sum.faction.id.1 
               0.008772033               -0.042947276 
  absdiff.sum.faction.id.2   absdiff.sum.faction.id.3 
              -0.388103140               -1.042268768 
  absdiff.sum.faction.id.4                  nodecovar 
               1.239016236                2.849464247 
Starting unconstrained MCMC...
Back from unconstrained MCMC.
New interval = 256.
Average estimating function values:
                       sum                    nonzero 
                3447.68542                  154.00767 
nodefactor.sum.leader.TRUE   absdiff.sum.faction.id.1 
                 590.73146                  -72.32737 
  absdiff.sum.faction.id.2   absdiff.sum.faction.id.3 
                 -11.52174                  -10.90281 
  absdiff.sum.faction.id.4                  nodecovar 
                2675.17391                  716.68044 
Starting MCMLE Optimization...
Optimizing with step length 0.0048.
Using lognormal metric (see control.ergm function).
Using log-normal approx (no optim)
The log-likelihood improved by 1.8465.
Distance from origin on tolerance region scale: 1577810 (previously 8881909).
Estimating equations are not within tolerance region.

Iteration 3 of at most 50 with parameter:
                       sum                    nonzero 
               1.348254492               -9.596580946 
nodefactor.sum.leader.TRUE   absdiff.sum.faction.id.1 
               0.009971824                1.320313760 
  absdiff.sum.faction.id.2   absdiff.sum.faction.id.3 
               1.155497910                2.751808842 
  absdiff.sum.faction.id.4                  nodecovar 
               1.250919233                2.910815511 
Starting unconstrained MCMC...
Back from unconstrained MCMC.
New interval = 512.
Average estimating function values:
                       sum                    nonzero 
              11914.616858                 138.003831 
nodefactor.sum.leader.TRUE   absdiff.sum.faction.id.1 
                856.229885                3083.386973 
  absdiff.sum.faction.id.2   absdiff.sum.faction.id.3 
                930.532567                7620.409962 
  absdiff.sum.faction.id.4                  nodecovar 
                 -9.996169                2745.809704 
Starting MCMLE Optimization...
Optimizing with step length 0.0001.
Using lognormal metric (see control.ergm function).
Using log-normal approx (no optim)
The log-likelihood improved by 0.0018.
Distance from origin on tolerance region scale: 11313874 (previously 5456921050).
Estimating equations are not within tolerance region.

Iteration 4 of at most 50 with parameter:
                       sum                    nonzero 
               1.347916421              -10.095197103 
nodefactor.sum.leader.TRUE   absdiff.sum.faction.id.1 
               0.009983863                1.320682211 
  absdiff.sum.faction.id.2   absdiff.sum.faction.id.3 
               1.156358318                2.752147456 
  absdiff.sum.faction.id.4                  nodecovar 
               0.752303075                2.910297210 
Starting unconstrained MCMC...
Back from unconstrained MCMC.
New interval = 1024.
Average estimating function values:
                       sum                    nonzero 
              11920.056338                 138.014085 
nodefactor.sum.leader.TRUE   absdiff.sum.faction.id.1 
                856.595070                3069.640845 
  absdiff.sum.faction.id.2   absdiff.sum.faction.id.3 
                933.390845                7635.250000 
  absdiff.sum.faction.id.4                  nodecovar 
                 -9.982394                2746.000645 
Starting MCMLE Optimization...
Optimizing with step length < 0.0001.
Using lognormal metric (see control.ergm function).
Using log-normal approx (no optim)
The log-likelihood improved by 0.0030.
Distance from origin on tolerance region scale: 48682819 (previously 48681834).
Estimating equations are not within tolerance region.
Quitting from lines 765-771 (valued.Rmd) 
Error: processing vignette 'valued.Rmd' failed with diagnostics:
MCMLE estimation stuck. There may be excessive correlation between model terms, suggesting a poor model for the observed data. If target.stats are specified, try increasing SAN parameters.
--- failed re-building 'valued.Rmd'

SUMMARY: processing the following file failed:
  'valued.Rmd'

Error: Vignette re-building failed.
Execution halted