⚡ Bolt: Remove redundant matrix inversions in vuongtest.R

[seonghobae]

💡 What: Replaced the return of the inverse matrix A with the original variance-covariance matrix tmpvc (named Ainv) in calcAB(). Updated calcLambda() to use Ainv directly instead of doing chol2inv(chol(AB1$A)) and chol2inv(chol(AB2$A)).
🎯 Why: In calcAB(), we calculated A <- chol2inv(chol(tmpvc)). In calcLambda(), we were doing chol2inv(chol(AB1$A)), which mathematically is just calculating the inverse of the inverse, bringing us back to tmpvc. This caused unnecessary O(n^3) matrix inversions, which are highly expensive for large matrices.
📊 Impact: Reduces execution time for vuongtest() by eliminating redundant matrix inversions, especially noticeable when dealing with large model variance-covariance matrices. Removes unnecessary numerical instability.
🔬 Measurement: Benchmark vuongtest() with large lavaan or mirt models; execution time and cpu load should drop significantly for the variance test calculations.

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PR created automatically by Jules for task 17702471422863492329 started by @seonghobae

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