id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_rtsqvklk3bczbpnpk67b4whhly	Olav Vassend	The philosophical significance of Stein's paradox	2017	35	.pdf	application/pdf	12039	738	60	have lower expected mean-squared error than any other unbiased estimator that is a linear time, and your goal is to minimize expected error across the three estimates, MLE is result shows that, under quadratic loss, the best translation invariant estimator of normal means, namely MLE, is dominated by shrinkage estimators that are not translation invariant and not shrinkage estimator is shown to have lower expected mean squared error than straight MLE. that there are shrinkage estimators that dominate MLE; this result obviously doesn't allow you to Are there any shrinkage estimators that are admissible and that dominate MLE? estimation problems and wants to minimize her expected sum of squared errors across the three. As noted, MLE is admissible when you estimate the value of a single parameter. dominates MLE in single-parameter estimation just means that there is no shrinkage estimator values if shrinkage estimators are to have lower expected error than MLE (Guttmann 1982).	./cache/work_rtsqvklk3bczbpnpk67b4whhly.pdf	./txt/work_rtsqvklk3bczbpnpk67b4whhly.txt