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Refers to an estimator of a population parameter that "hits the true value" on average. That is, a function of the observed data $\hat{\theta}$ is an unbiased estimator of a parameter $\theta$ if $E(\hat{\theta}) = \theta$. The simplest example of an unbiased estimator is the sample mean as an estimator of the population mean.

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UMVUE for $\theta$ where $X \sim Unif\{1 ,\ldots, \theta\}$

Please see the Lehmann Scheffe theorem (Theorem 2 in http://www.stat.unc.edu/faculty/cji/lecture9.pdf), which states that if $U$ is a complete sufficient statistic, and $T$ is an unbiased estimator, t …
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Stein's estimator vs James-Stein estimator

I don't think there is a difference. Stein's result is to show inadmissibility of the mean in the case of multivariate normal. James-Stein developed the estimator for quadratic loss. The James-Stein e …
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