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

> ### Name: umx
> ### Title: Helper Functions for Structural Equation Modelling in OpenMx
> ### Aliases: umx umx-package
> 
> ### ** Examples
> 
> require("umx")
> data(demoOneFactor)
> myData = mxData(cov(demoOneFactor), type = "cov", numObs = nrow(demoOneFactor))
> latents = c("G")
> manifests = names(demoOneFactor)
> m1 <- umxRAM("One Factor", data = myData,
+ 	umxPath(latents, to = manifests),
+ 	umxPath(var = manifests),
+ 	umxPath(var = latents  , fixedAt=1)
+ )
A latent variable 'G' was created. 
Running One Factor with 10 parameters
?umxSummary showEstimates='raw|std', digits, report= 'html', filter= 'NS' & more
[1] "χ²(5) = 7.39, p = 0.193; CFI = 0.999; TLI = 0.999; RMSEA = 0.031"
> 
> # umx added informative labels, created starting values, 
> # Ran you model (if autoRun is on), and displayed a brief summary
> # including a comparison if you modified a model...!
> 
> # Let's get some journal-ready fit information
> 
> umxSummary(m1) 
?umxSummary showEstimates='raw|std', digits, report= 'html', filter= 'NS' & more


|name       | Estimate|   SE|
|:----------|--------:|----:|
|G_to_x1    |     0.40| 0.02|
|G_to_x2    |     0.50| 0.02|
|G_to_x3    |     0.58| 0.02|
|G_to_x4    |     0.70| 0.02|
|G_to_x5    |     0.80| 0.03|
|x1_with_x1 |     0.04| 0.00|
|x2_with_x2 |     0.04| 0.00|
|x3_with_x3 |     0.04| 0.00|
|x4_with_x4 |     0.04| 0.00|
|x5_with_x5 |     0.04| 0.00|
|G_with_G   |     1.00| 0.00|
[1] "χ²(5) = 7.39, p = 0.193; CFI = 0.999; TLI = 0.999; RMSEA = 0.031"
> umxSummary(m1, show = "std") #also display parameter estimates 
?umxSummary showEstimates='raw|std', digits, report= 'html', filter= 'NS' & more


|name       | Std.Estimate| Std.SE|CI                |
|:----------|------------:|------:|:-----------------|
|G_to_x1    |         0.89|   0.01|0.89 [0.87, 0.91] |
|G_to_x2    |         0.93|   0.01|0.93 [0.92, 0.95] |
|G_to_x3    |         0.94|   0.01|0.94 [0.93, 0.95] |
|G_to_x4    |         0.96|   0.00|0.96 [0.95, 0.97] |
|G_to_x5    |         0.97|   0.00|0.97 [0.97, 0.98] |
|x1_with_x1 |         0.21|   0.02|0.21 [0.17, 0.24] |
|x2_with_x2 |         0.13|   0.01|0.13 [0.11, 0.15] |
|x3_with_x3 |         0.11|   0.01|0.11 [0.09, 0.13] |
|x4_with_x4 |         0.07|   0.01|0.07 [0.06, 0.09] |
|x5_with_x5 |         0.05|   0.01|0.05 [0.04, 0.07] |
|G_with_G   |         1.00|   0.00|1 [1, 1]          |
[1] "χ²(5) = 7.39, p = 0.193; CFI = 0.999; TLI = 0.999; RMSEA = 0.031"
> # You can get the coefficients of an MxModel with coef(), just like for lm etc.
> coef(m1)
   G_to_x1    G_to_x2    G_to_x3    G_to_x4    G_to_x5 x1_with_x1 x2_with_x2 
0.39675479 0.50315708 0.57666362 0.70207039 0.79545313 0.04073255 0.03794395 
x3_with_x3 x4_with_x4 x5_with_x5 
0.04074551 0.03930826 0.03621450 
> 
> # ==================
> # = Model updating =
> # ==================
> # Can we set the loading of X5 on G to zero?
> m2 = omxSetParameters(m1, labels = "G_to_x1", values = 0, free = FALSE, name = "no_g_on_X5")
> m2 = mxRun(m2)
Running no_g_on_X5 with 9 parameters
> # Compare the two models
> umxCompare(m1, m2)


|Model      | EP|∆ -2LL     |∆ df |p       |        AIC|Compare with Model |
|:----------|--:|:----------|:----|:-------|----------:|:------------------|
|One Factor | 10|           |     |        |  -2.606207|                   |
|no_g_on_X5 |  9|750.416577 |1    |< 0.001 | 745.810370|One Factor         |
> 
> # Use umxModify to do the same thing in 1-line
> m2 = umxModify(m1, "G_to_x1", name = "no_effect_of_g_on_X5", comparison = TRUE)
Running no_effect_of_g_on_X5 with 9 parameters
?umxSummary showEstimates='raw|std', digits, report= 'html', filter= 'NS' & more


|name       | Estimate|   SE|
|:----------|--------:|----:|
|G_to_x2    |     0.50| 0.02|
|G_to_x3    |     0.58| 0.02|
|G_to_x4    |     0.70| 0.02|
|G_to_x5    |     0.80| 0.03|
|x1_with_x1 |     0.20| 0.01|
|x2_with_x2 |     0.04| 0.00|
|x3_with_x3 |     0.04| 0.00|
|x4_with_x4 |     0.04| 0.00|
|x5_with_x5 |     0.04| 0.00|
|G_with_G   |     1.00| 0.00|
[1] "χ²(6) = 757.81, p < 0.001; CFI = 0.798; TLI = 0.663; RMSEA = 0.501"
TLI is worse than desired
RMSEA is worse than desired


|Model                | EP|∆ -2LL     |∆ df |p       |        AIC|Compare with Model |
|:--------------------|--:|:----------|:----|:-------|----------:|:------------------|
|One Factor           | 10|           |     |        |  -2.606207|                   |
|no_effect_of_g_on_X5 |  9|750.416577 |1    |< 0.001 | 745.810370|One Factor         |
> 
> # ========================
> # = Confidence intervals =
> # ========================
> 
> # umxSummary() will show these, but you can also use the confint() function
> confint(m1) # OpenMx's SE-based confidence intervals
Wald type confidence intervals (see ?mxCI for likelihood-based CIs)
                 2.5%      97.5%
G_to_x1    0.36633882 0.42717077
G_to_x2    0.46749358 0.53882058
G_to_x3    0.53666576 0.61666147
G_to_x4    0.65510313 0.74903765
G_to_x5    0.74328665 0.84761961
x1_with_x1 0.03523626 0.04622885
x2_with_x2 0.03246119 0.04342671
x3_with_x3 0.03458563 0.04690539
x4_with_x4 0.03264703 0.04596949
x5_with_x5 0.02902628 0.04340272
> umxConfint(m1, parm = 'all', run = TRUE) # likelihood-based CIs
Running One Factor with 10 parameters

 *** caught segfault ***
address fc120350, cause 'memory not mapped'

Traceback:
 1: runHelper(model, frontendStart, intervals, silent, suppressWarnings,     unsafe, checkpoint, useSocket, onlyFrontend, useOptimizer)
 2: mxRun(model, suppressWarnings = TRUE)
 3: omxParallelCI(model = model, run = TRUE, verbose = verbose, independentSubmodels = FALSE,     optimizer = optimizer)
 4: omxRunCI(object, optimizer = optimizer)
 5: umxConfint(m1, parm = "all", run = TRUE)
An irrecoverable exception occurred. R is aborting now ...