Charles Stein (statistician)

Charles M. Stein (born March 22, 1920), an American mathematical statistician, is emeritus professor of statistics at Stanford University. He received his Ph.D in 1947 at Columbia University with advisor Abraham Wald. He is known for Stein's paradox in decision theory which shows that ordinary least squares estimates can be uniformly improved when many parameters are estimated, and for Stein's method, a way of proving theorems such as the Central Limit Theorem. He is a member of the National Academy of Sciences.

Works

• Approximate Computation of Expectations, Institute of Mathematical Statistics, Hayward, CA, 1986.

Interviews

• Morris H. DeGroot A Conversation with Charles Stein, Statistical Science, Vol. 1, No. 4 (Nov., 1986), pp. 454–462
• Charles Stein: The Invariant, the Direct and the "Pretentious"

See also

• James–Stein estimator
• Stein's lemma
• Stein's method
• Stein's unbiased risk estimate
• Stein's loss

External links

• Charles M. Stein at the Mathematics Genealogy Project
• National University of Singapore Program Honoring Prof. Stein
• Another photograph
• Another photograph