Stein's example
In decision theory and estimation theory, Stein's example (also known as Stein's phenomenon or Stein's paradox) is the observation that when three or more parameters are estimated simultaneously, there exist combined estimators more accurate on average (that is, having lower expected mean squared error) than any method that handles the parameters separately. It is named after Charles Stein of Stanford University, who discovered the phenomenon in 1955.
Stein's example - Wikipedia Jump to content From Wikipedia, the free encyclopedia Phenomenon in decision theory and estimation theory In decision theory and estimation theory , Stein's example (also known as Stein's phenomenon or Stein's paradox ) is the observation that when three or more parameters are estimated simultaneously, there exist combined estimators more accurate on average (that is, having lower expected mean squared error ) than any method that handles the parameters separately. It is named after Charles Stein of Stanford University , who discovered the phenomenon in 1955. [
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