For estimating a normal variance under squared error loss function it is well known that the best affine (location and scale) equivariant estimator, which is better than the maximum likelihood estimator as well as the unbiased estimator, is also inadmissible. The improved estimators, e.g., Stein type, Brown type and Brewster-Zidek type, are all scale equivariant but not location invariant. Lately a good amount of research has been done to compare the improved estimators in terms of risk, but very little attention had been paid to compare these estimators in terms of Pitman nearness criterion. In this paper we have undertaken a comprehensive study to compare various variance estimators in terms of Pitman nearness criterion, which has long been over due, and have made some interesting observations in the process.
