Is SAS telling something about V matrix in PROC MIXED?

[Rick_SAS]

To expand on @SteveDenham's remark, from a matrix perspective the mixed-modeling procedures in SAS are written to solve the general model Y=X*beta +Z*gamma + epsilon where gamma ~ MVN(0,G) and epsilon~MVN(0,R),

In this formulation, the input matrices are X, Z, G, and R. These correspond to the various statements in the mixed-modeling procedures. In the simplest examples, the MODELS stmt defines X, the RANDOM stmt defines Z, the options to the RANDOM stmt define G, and the REPEATED stmt defines R.  

If you ASSUME that this model holds (including that G and R are valid SPD covariance matrices), then it FOLLOWS that the marginal model is Y~MVN(X*beta, V) where V=ZGZ` + R is positive definite. Thus you never need to check whether V is SPD when G and R are valid covariance matrices.

When you use the NOBOUNDS option, you are declaring that you don't want SAS to enforce PD during estimation. I'm sure there are valid statistical reasons why this might be desired, but from a mathematical perspective it really muddies the waters.