  This paper focuses on three contributions. First, a connection between the
result, proposed by Stoica and Babu, and the recent information theoretic
results, the worst additive noise lemma and the isoperimetric inequality for
entropies, is illustrated. Second, information theoretic and estimation
theoretic justifications for the fact that the Gaussian assumption leads to the
largest Cram\'{e}r-Rao lower bound (CRLB) is presented. Third, a slight
extension of this result to the more general framework of correlated
observations is shown.
