OpenMx Help
hiliang
Joined: 11/17/2014
OpenMx performance on CentOS server
I just run the demo script of the package and I don't modify the script.
when I run the demo script AlternativeApproaches.R on my computer, the running cpu is around 100% and completed in 10 seconds.
input:
time Rscript AlternativeApproaches.R
output:
real 0m2.431s
user 0m3.752s
sys 0m0.093s
But when I run the script on my company CentOS server, the running cpu is above 500% and completed in more than 15 minutes.
input:
time Rscript AlternativeApproaches.R
output:
real 2m39.438s
user 15m6.753s
sys 0m2.392s
- Read more about OpenMx performance on CentOS server
- 6 comments
- Log in or register to post comments
Pontifex
Joined: 03/02/2015
Installation error on R 3.1.2 for Linux
I'm attempting to install OpenMx in R 3.1.2 on a machine running Linux Mint 17.1 (a fork of Ubuntu 14.04). After sourcing the "getOpenMx.R" script, R downloads the package, but then hits the following error:
* installing *source* package ‘OpenMx’ ...
Change default C/C++ compiler and default compile flags by editing /usr/lib/R/etc/Makeconf
./configure: line 113: curl: command not found
ERROR: configuration failed for package ‘OpenMx’
* removing ‘~/R/x86_64-pc-linux-gnu-library/3.1/OpenMx’
Warning message:
- Read more about Installation error on R 3.1.2 for Linux
- 2 comments
- Log in or register to post comments
HYOSHIN
Joined: 02/23/2015
SEM, Binary and Categorical Data in independent variables
Dear all, Please help me fixing this problem.
The data set has (please see example diagram)
+ 3 continuous variables(X1, X2, X3) for a latent variable (intercept)
+ 3 mediators (one binary X8 and two categorical variables X6, X7)
+ 1 dependent variable (X4).
This coding was based on the post about Categorical Data in both independent and dependent variables http://openmx.psyc.virginia.edu/thread/3883
When I run SEM.R model I have following error message.
Error in mxRAMObjective(A = "A", S = "S", M = "M", thresholds = "Threshold") :
karobro
Joined: 01/16/2013
fitfunction is not finite
Hi,
I am trying to fit a saturated twin model to 9 ordinal variables (representing age at observation), in which participants have either 1, 2 or 3 observations each. Thus, there is quite a bit of missing data.
When running the model I get the following error: Sat5.fitfunction is not finite.
Here is info about version and platform:
OpenMx version: 2.0.1.4157
R version: R version 3.1.1 (2014-07-10)
Platform: x86_64-w64-mingw32
Default optimiser: NPSOL
- Read more about fitfunction is not finite
- 4 comments
- Log in or register to post comments
janneadolf
Joined: 02/06/2015
Access Kalman filter generated process state estimates online (mxExpectationStateSpace)
I am using the Kalman filter implementation (mxExpectationStateSpace) to fit a time-discrete vector auto-regressive model to single subjects' multivariate time series. If I'm not mistaken, the Kalman filter generates (predicted and updated) process state estimates for each but the first time point. Is it possible to pull these state estimates out online while the data are being filtered?
wuhao_osu
Joined: 09/07/2010
Background of data set in OpenMx
I can see several twin data sets that come with OpenMx, for example, the DZO data described by following page:
http://openmx.psyc.virginia.edu/docs/OpenMx/latest/_static/Rdoc/dzoData.html
Would anyone please provide more background about this data? The sample size seems to indicate that it is not simulated data, but no descriptions are given for the variables.
I would appreciate it. Thanks.
- Read more about Background of data set in OpenMx
- 2 comments
- Log in or register to post comments
Charlotte
Joined: 07/02/2012
CharlesD
Joined: 04/30/2013
Problem with definition variables with state space expectation?
Am I doing something wrong? I was surprised when my model seemed to be ignoring my definition variables, but then I also notice that mxEval interprets them all as NA... this is using a build from yesterday, 1st Feb 2015, on 64 bit windows.
data(demoOneFactor)
nvar <- ncol(demoOneFactor)
varnames <- colnames(demoOneFactor)
demoOneFactorInputs <- cbind(demoOneFactor, V1=rnorm(nrow(demoOneFactor)))
ssModel <- mxModel(model="State Space Inputs Manual Example",
mxMatrix("Full", 1, 1, TRUE, .3, name="A"),
mxMatrix("Full", 1, 1, TRUE, values=1, name="B"),
Ryan
Joined: 02/08/2014
Protection stack too large
Dear all,
Did anyone have a warning like:
"Warning message:
In runHelper(model, frontendStart, intervals, silent, suppressWarnings, :
Protection stack too large; report this problem to the OpenMx forum"
Does anyone know how we can handle this?
Other information:
- The version of OpenMx: 2.0.0-4004 MASS_7.3-35
- The version of R: 3.1.2
- The operating system and architecture: x86_64, Apple OSX 10.8.5.
- R syntax that brings this warning is a command in "metaSEM": --tssem1--
Thanks!
- Read more about Protection stack too large
- 10 comments
- Log in or register to post comments
CharlesD
Joined: 04/30/2013
Error in omxAssignFirstParameters / omxSetParameters... 'labels' argument must not contain duplicate values
This seems to be occurring when I try and constrain values across different matrices by label, then use omxAssignFirstParameters to set starting values - omxSetParameters gives the " 'labels' must not contain duplicate values" error. When I use the same label within the same matrix there is no problem. When browsing into the error, I see that indeed, the labels object within omxSetParameters contains duplicates only when they are specified from different matrices.
Pagination
- Previous page
- Page 21
- Next page