ENH: GLS fix for very large models

GLS can now handle very large models with diagonal sigma matrices.  This was done by removing the need for a full nobs by nobs covariance when sigma is input as a scalar or vector.

Test coverage for large model with 100,000 observations.  This would require > 64GB of main memory in previous GLS code.
Simplified branching in GLS.whiten

Removed one level of an if statement in GLS.whiten and reordered
from lowest to highest for the dimension
TST GLS_large_data lower samplesize (no memory test anymore), fix typo
Merge branch 'gls-large-data-size' closes #1176