Stan warnings
13 warnings generated.
clang: warning: libstdc++ is deprecated; move to libc++ with a minimum deployment target of OS X 10.9
[I 21:25:13.800 NotebookApp] Saving file at /Frank's model.ipynb
Iteration: 1 / 10000 [ 0%] (Warmup) (Chain 0)
Iteration: 1 / 10000 [ 0%] (Warmup) (Chain 1)
Iteration: 1 / 10000 [ 0%] (Warmup) (Chain 2)
Iteration: 1 / 10000 [ 0%] (Warmup) (Chain 3)
Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
Exception thrown at line 34: lkj_corr_log: y is not positive definite.
If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
Exception thrown at line 34: lkj_corr_log: y is not positive definite.
If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
Exception thrown at line 34: lkj_corr_log: y is not positive definite.
If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
Exception thrown at line 34: lkj_corr_log: y is not positive definite.
If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
Exception thrown at line 34: lkj_corr_log: y is not positive definite.
If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
Exception thrown at line 34: lkj_corr_log: y is not positive definite.
If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
Exception thrown at line 34: lkj_corr_log: y is not positive definite.
If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
Exception thrown at line 34: lkj_corr_log: y is not positive definite.
If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.
Informational Message: The current Metropolis proposal is about to be rejected because of the following issue:
Exception thrown at line 34: lkj_corr_log: y is not positive definite.
If this warning occurs sporadically, such as for highly constrained variable types like covariance matrices, then the sampler is fine,
but if this warning occurs often then your model may be either severely ill-conditioned or misspecified.