I expected this to be able to run with no issues since it's conjugate.
What actually happened instead?
The sampler threw an error:
Defining model
Building model
Setting data and initial values
Running calculate on model
[Note] Any error reports that follow may simply reflect missing values in model variables.
Checking model sizes and dimensions
Checking model calculations
Compiling
[Note] This may take a minute.
[Note] Use 'showCompilerOutput = TRUE' to see C++ compilation details.
Error: Error, wrong number of indices provided for dep_dmnorm_identity_coeff[iDep].
This occurred for: dep_dmnorm_identity_coeff[iDep]
This was part of the call: dep_dmnorm_identity_coeff[iDep] <<- Interm_4091[1, 1]
Environment
R: 4.1.2
Nimble: 0.12.1
Project that demonstrates the issue
See code above. I found that if non-Gibbs samplers are used for the covariance matrices, then the sampler works. If there is a workaround, please let me know!
What did you do?
I wanted to conduct a mixture of multivariate normals problem. The code I have is as follows:
What did you expect to happen?
I expected this to be able to run with no issues since it's conjugate.
What actually happened instead?
The sampler threw an error:
Environment
Project that demonstrates the issue
See code above. I found that if non-Gibbs samplers are used for the covariance matrices, then the sampler works. If there is a workaround, please let me know!