Seymour Geisser
American statistician (1929–2004) / From Wikipedia, the free encyclopedia
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Seymour Geisser (October 5, 1929 – March 11, 2004) was an American statistician noted for emphasizing predictive inference. In his book Predictive Inference: An Introduction, he held that conventional statistical inference about unobservable population parameters amounts to inference about things that do not exist, following the work of Bruno de Finetti. He also pioneered the theory of cross-validation.
With Samuel Greenhouse, he developed the Greenhouse–Geisser correction, which is now widely used in the analysis of variance to correct for violations of the assumption of compound symmetry.[1]
He testified as an expert on interpretation of DNA evidence in more than 100 civil and criminal trials. He held that prosecutors often relied on flawed statistical models. On that topic, he wrote "Statistics, Litigation and Conduct Unbecoming" in the book Statistical Science in the Courtroom, edited by Joe [Joseph Louis] Gastwirth (Springer Verlag, 2000).