Predictive inference is an interpretation of probability that emphasizes the prediction of future observations based on past observations.
Initially, predictive inference based on observable parameters was the main function of probability, but it fell out of favor in the 20th century due to a new parametric approach pioneered by Bruno de Finetti. The approach modeled phenomena as a physical system observed with error (e.g., celestial mechanics). De Finetti's idea of exchangeability–-that future observations should behave like past observations–-came to the attention of the English-speaking world with the 1974 translation of his 1937 book Foresight: its Logical Laws, Its Subjective Sources (French: La Prévision: ses lois logiques, ses sources subjectives) and has since been propounded by such statisticians as Seymour Geisser.[1]
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