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

> ### Name: mxBootstrap
> ### Title: Repeatedly estimate model using resampling with replacement
> ### Aliases: mxBootstrap
> 
> ### ** Examples
> 
> library(OpenMx)
> 
> data(multiData1)
> 
> manifests <- c("x1", "x2", "y")
> 
> biRegModelRaw <- mxModel(
+   "Regression of y on x1 and x2",
+   type="RAM",
+   manifestVars=manifests,
+   mxPath(from=c("x1","x2"), to="y", 
+          arrows=1, 
+          free=TRUE, values=.2, labels=c("b1", "b2")),
+   mxPath(from=manifests, 
+          arrows=2, 
+          free=TRUE, values=.8, 
+          labels=c("VarX1", "VarX2", "VarE")),
+   mxPath(from="x1", to="x2",
+          arrows=2, 
+          free=TRUE, values=.2, 
+          labels=c("CovX1X2")),
+   mxPath(from="one", to=manifests, 
+          arrows=1, free=TRUE, values=.1, 
+          labels=c("MeanX1", "MeanX2", "MeanY")),
+   mxData(observed=multiData1, type="raw"))
> 
> biRegModelRawOut <- mxRun(biRegModelRaw)
Running Regression of y on x1 and x2 with 9 parameters
Warning: In model 'Regression of y on x1 and x2' Optimizer returned a non-zero status code 6. The model does not satisfy the first-order optimality conditions to the required accuracy, and no improved point for the merit function could be found during the final linesearch (Mx status RED)
> 
> boot <- mxBootstrap(biRegModelRawOut, 10)   # start with 10
Running Regression of y on x1 and x2 with 9 parameters
> summary(boot)
Warning: Only 30% of the bootstrap replications converged. Accuracy is much less than the 10 replications requested
Summary of Regression of y on x1 and x2 
 
free parameters:
     name matrix row col  Estimate   Std.Error     25.0%     75.0%
1      b1      A   y  x1 0.4479123 0.025008068 0.4219408 0.4247656
2      b2      A   y  x2 0.4327148 0.004689155      -Inf      -Inf
3   VarX1      S  x1  x1 1.1364299 0.129085599 1.0094452 1.0132536
4 CovX1X2      S  x1  x2 0.5811057 0.098846024 0.5405107 0.5573484
5   VarX2      S  x2  x2 1.5556043 0.087720762      -Inf      -Inf
6    VarE      S   y   y 1.4119922 0.141913446 1.3422834 1.3919889
7  MeanX1      M   1  x1 0.9848940 0.012015165      -Inf      -Inf
8  MeanX2      M   1  x2 1.9741802 0.022110541      -Inf 1.9639525
9   MeanY      M   1   y 2.5530358 0.041396733 2.5094522 2.5315910

Model Statistics: 
               |  Parameters  |  Degrees of Freedom  |  Fit (-2lnL units)
       Model:              9                   1491              4577.998
   Saturated:              9                   1491                    NA
Independence:              6                   1494                    NA
Number of observations/statistics: 500/1500

Information Criteria: 
      |  df Penalty  |  Parameters Penalty  |  Sample-Size Adjusted
AIC:       1595.998               4595.998                       NA
BIC:      -4687.983               4633.929                 4605.362
CFI: NA 
TLI: 1   (also known as NNFI) 
RMSEA:  0  [95% CI (NA, NA)]
Prob(RMSEA <= 0.05): NA
To get additional fit indices, see help(mxRefModels)
timestamp: 2017-11-06 22:28:35 
Wall clock time: 2.365308 secs 
OpenMx version number: 2.8.3 
Need help?  See help(mxSummary) 

> 
> # Looks good, now do the rest
> ## Not run: boot <- mxBootstrap(boot)
> summary(boot)
Warning: Only 30% of the bootstrap replications converged. Accuracy is much less than the 10 replications requested
Summary of Regression of y on x1 and x2 
 
free parameters:
     name matrix row col  Estimate   Std.Error     25.0%     75.0%
1      b1      A   y  x1 0.4479123 0.025008068 0.4219408 0.4247656
2      b2      A   y  x2 0.4327148 0.004689155      -Inf      -Inf
3   VarX1      S  x1  x1 1.1364299 0.129085599 1.0094452 1.0132536
4 CovX1X2      S  x1  x2 0.5811057 0.098846024 0.5405107 0.5573484
5   VarX2      S  x2  x2 1.5556043 0.087720762      -Inf      -Inf
6    VarE      S   y   y 1.4119922 0.141913446 1.3422834 1.3919889
7  MeanX1      M   1  x1 0.9848940 0.012015165      -Inf      -Inf
8  MeanX2      M   1  x2 1.9741802 0.022110541      -Inf 1.9639525
9   MeanY      M   1   y 2.5530358 0.041396733 2.5094522 2.5315910

Model Statistics: 
               |  Parameters  |  Degrees of Freedom  |  Fit (-2lnL units)
       Model:              9                   1491              4577.998
   Saturated:              9                   1491                    NA
Independence:              6                   1494                    NA
Number of observations/statistics: 500/1500

Information Criteria: 
      |  df Penalty  |  Parameters Penalty  |  Sample-Size Adjusted
AIC:       1595.998               4595.998                       NA
BIC:      -4687.983               4633.929                 4605.362
CFI: NA 
TLI: 1   (also known as NNFI) 
RMSEA:  0  [95% CI (NA, NA)]
Prob(RMSEA <= 0.05): NA
To get additional fit indices, see help(mxRefModels)
timestamp: 2017-11-06 22:28:35 
Wall clock time: 2.365308 secs 
OpenMx version number: 2.8.3 
Need help?  See help(mxSummary) 

> 
> # examine replication 3
> boot3 <- mxBootstrap(boot, only=3)
Running Regression of y on x1 and x2 with 9 parameters
Error: The job for model 'Regression of y on x1 and x2' exited abnormally with the error message: fit is not finite (0: The continuous part of the model implied covariance (loc2) is not positive definite in data 'Regression of y on x1 and x2.data' row 317. Detail:
covariance =  matrix(c(    # 3x3
   0,   0,   0
,   0,   0,   0
,   0,   0, 0.744529), byrow=TRUE, nrow=3, ncol=3)

)
Execution halted